The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed...The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed out from such logic system. This article aims to rearticulate the underlying lucid multi-dimensional logic system, which faded in obscurity only because of time-out loss of the mid-right concept. Retracing this past tacit but important concept could uncover a multi-dimensional system over a point relating to all matters while capturing the central core of the matter. The seemingly unmanageable multidimensional logic was strengthened by verification processes which affirmed its further extensions, and made up the language of the people, the concepts of yin-yang(阴阳), and the development of extensions of Ba Gua(八卦) derivatives, which furthered the interpretation of the space-time properties and Chinese medicine.展开更多
Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial...Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial for acquiring stable NiSe2-based materials for sodium-ion batteries(SIBs),Herein,a stress dissipation strategy driven by architecture engineering is proposed,which can achieve ultrafast and ultralong sodium storage properties.Different from the conventional sphere-like or rod-like architecture,the three-dimensional(3D)flower-like NiSe_(2)@C composite is delicately designed and assembled with onedimensional nanorods and carbon framework.More importantly,the fundamental mechanism of improved structure stability is unveiled by simulations and experimental results simultaneously.It demonstrates that this designed multidimensional flower-like architecture with dispersed nanorods can balance the structural mismatch,avoid concentrated local strain,and relax the internal stress,mainly induced by the unavoidable volume variation during the repeated conversion processes.Moreover,it can provide more Na^(+)-storage sites and multi-directional migration pathways,leading to a fast Na^(+)-migration channel with boosted reaction kinetic.As expected,it delivers superior rate performance(441 mA h g^(-1)at 5.0 A g^(-1))and long cycling stability(563 mA h g^(-1)at 1.0 A g^(-1)over 1000 cycles)for SIBs.This work provides useful insights for designing high-performance conversion-based anode materials for SIBs.展开更多
This paper explores whole-process engineering consulting,including its application models in public buildings and elderly-friendly projects,such as service integration and whole lifecycle management.It also addresses ...This paper explores whole-process engineering consulting,including its application models in public buildings and elderly-friendly projects,such as service integration and whole lifecycle management.It also addresses the construction of multi-dimensional collaborative theoretical models,public space streamline organization,and other aspects,emphasizing the importance of multi-dimensional collaboration.Additionally,it highlights the role of talent cultivation and digital transformation in enhancing project efficiency.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
A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source di...A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.展开更多
During the critical transformation period of landscape architecture major after the adjustment of disciplinary structure and the changes in market demand,private colleges and universities,as important places for culti...During the critical transformation period of landscape architecture major after the adjustment of disciplinary structure and the changes in market demand,private colleges and universities,as important places for cultivating local talents,have pain points such as uneven quality of teachers and students and weak innovation and practice.The practice system with“multi-dimensional Integration”integrates four dimensions:interdisciplinary integration,spatial and temporal intersection,historical inheritance,and behavioral activity,deepens the disciplinary connotation,and integrates the three elements of nature,humanity,and technology,aiming to provide a new path for private colleges and universities to cultivate application-oriented and compound talents with innovative capabilities.In terms of optimizing talent cultivation and adapting to industry changes,this system provides thinking and reference for landscape architecture major,helping the major reshape its core competitiveness and promoting educational innovation and industry development.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)feat...Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)featured chromophore(HBT-DPI)that shows flexible emission tunability via the multidimensional regulation of intra-and intermolecular H-bonds.The feature of switchable intramolecular Hbonds is induced via incorporating several hydrogen bond acceptors and donors into one single HBT-DPI molecule,allowing the“turn on/off”of ESIPT process by forming isomers with distinct intramolecular Hbonds configurations.In response to different external H-bonding environments,the obtained four types of crystal/cocrystals vary in the contents of isomers and the molecular packing modes,which are mainly guided by the intermolecular H-bonds,exhibiting non-emissive features or emissions ranging from green to orange.Utilizing the feature of intermolecular H-bond guided molecular packing,we demonstrate the utility of this fluorescent material for visualizing hydrophobic/hydrophilic areas on large-scale heterogeneous surfaces of modified poly(1,1-difluoroethylene)(PVDF)membranes and quantitatively estimating the surface hydrophobicity,providing a new approach for hydrophobicity/hydrophilicity monitoring and measurement.Overall,this study represents a new design strategy for constructing multi-dimensional hydrogen bond regulated ESIPT-based fluorescent materials that enable multiple emissions and unique applications.展开更多
Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction mode...Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends ...The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends on a deep understanding of customer behavior. This study proposes a theoretical framework for multi-dimensional customer behavior analysis, aiming to comprehensively capture customer behavioral characteristics in the digital environment. This framework integrates concepts of multi-source data including transaction history, browsing trajectories, social media interactions, and location information, constructing a theoretically more comprehensive customer profile. The research discusses the potential applications of this theoretical framework in precision marketing scenarios such as personalized recommendations, cross-selling, and customer churn prevention. Through analysis, the study points out that multi-dimensional analysis may significantly improve the targeting and theoretical conversion rates of marketing activities. However, the research also explores theoretical challenges that may be faced in the application process, such as data privacy and information overload, and proposes corresponding conceptual coping strategies. This study provides a new theoretical perspective on how businesses can optimize marketing decisions using big data thinking while respecting customer privacy, laying a foundation for future empirical research.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
The study constructed a multi-dimensional feedback mode integrating teacher feedback, peer feedback and network feedback, and applied it in the teaching of College English Writing. After 16 weeks of teaching, the stud...The study constructed a multi-dimensional feedback mode integrating teacher feedback, peer feedback and network feedback, and applied it in the teaching of College English Writing. After 16 weeks of teaching, the students in the multi-dimen-sional feedback class had significantly better overall writing scores than those in the teacher-feedback class. In terms of individual scores, multi-dimensional feedback played a better role in improving vocabulary and grammar than the class using teacher feed-back. However, there were no significant differences in the responses of writing tasks, coherence and cohesion. The study showed that most students were satisfied with the mode, believing that it was helpful to relieve writing anxiety, stimulate writing interest and improve their writing level.展开更多
Recently,multilevel structural carbon aerogels are deemed as attractive candidates for microwave absorbing materials.Nevertheless,excessive stack and agglomeration for low-dimension carbon nanomaterials inducing imped...Recently,multilevel structural carbon aerogels are deemed as attractive candidates for microwave absorbing materials.Nevertheless,excessive stack and agglomeration for low-dimension carbon nanomaterials inducing impedance mismatch are significant challenges.Herein,the delicate“3D helix-2D sheet-1D fiber-0D dot”hierarchical aerogels have been successfully synthesized,for the first time,by sequential processes of hydrothermal self-assembly and in-situ chemical vapor deposition method.Particularly,the graphene sheets are uniformly intercalated by 3D helical carbon nanocoils,which give a feasible solution to the mentioned problem and endows the as-obtained aerogel with abundant porous structures and better dielectric properties.Moreover,by adjusting the content of 0D core-shell structured particles and the parameters for growth of the 1D carbon nanofibers,tunable electromagnetic properties and excellent impedance matching are achieved,which plays a vital role in the microwave absorption performance.As expected,the optimized aerogels harvest excellent performance,including broad effective bandwidth and strong reflection loss at low filling ratio and thin thickness.This work gives valuable guidance and inspiration for the design of hierarchical materials comprised of dimensional gradient structures,which holds great application potential for electromagnetic wave attenuation.展开更多
Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility...Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility that considers multi-dimensional performance limit state parameters and makes a first attempt to develop fragility curves for a multi-span continuous (MSC) concrete girder bridge considering two performance limit state parameters: column ductility and transverse deformation in the abutments. The main purpose of this paper is to show that the performance limit states, which are compared with the seismic response parameters in the calculation of fragility, should be properly modeled as randomly interdependent variables instead of deterministic quantities. The sensitivity of fragility curves is also investigated when the dependency between the limit states is different. The results indicate that the proposed method can be used to describe the vulnerable behavior of bridges which are sensitive to multiple response parameters and that the fragility information generated by this method will be more reliable and likely to be implemented into transportation network loss estimation.展开更多
The simulation of hypersonic flows with fully unstructured(tetrahedral)grids has severe problems with respect to the prediction of stagnation region heating,due to the random face orientation without alignment to the ...The simulation of hypersonic flows with fully unstructured(tetrahedral)grids has severe problems with respect to the prediction of stagnation region heating,due to the random face orientation without alignment to the bow shock.To improve the accuracy of aero-heating predictions,three multi-dimensional approaches on unstructured grids are coupled in our Reynolds-averaged Navier-Stokes(RANS)solver,including multi-dimensional upwind flux reconstruction(MUP),multi-dimensional limiter(MLP-u2)and multi-dimensional gradient reconstruction(MLR).The coupled multi-dimensional RANS solver is validated by several typical verification and validation(V&V)cases,including hypersonic flows over a cylinder,a blunt biconic,and a double-ellipsoid,with commonly used prism/tetrahedral hybrid grids.Finally,the coupled multi-dimensional solver is applied to simulating the heat flux distribution over a 3D engineering configuration,i.e.a Hermes-like space shuttle model.The obtained numerical results are compared with experimental data.The predicted results demonstrate that the coupled multi-dimensional approach has a good prediction capability on aerodynamic heating over a wide range of complex engineering configurations.展开更多
Because the hydraulic directional valve usually works in a bad working environment and is disturbed by multi-factor noise,the traditional single sensor monitoring technology is difficult to use for an accurate diagnos...Because the hydraulic directional valve usually works in a bad working environment and is disturbed by multi-factor noise,the traditional single sensor monitoring technology is difficult to use for an accurate diagnosis of it.Therefore,a fault diagnosis method based on multi-sensor information fusion is proposed in this paper to reduce the inaccuracy and uncertainty of traditional single sensor information diagnosis technology and to realize accurate monitoring for the location or diagnosis of early faults in such valves in noisy environments.Firstly,the statistical features of signals collected by the multi-sensor are extracted and the depth features are obtained by a convolutional neural network(CNN)to form a complete and stable multi-dimensional feature set.Secondly,to obtain a weighted multi-dimensional feature set,the multi-dimensional feature sets of similar sensors are combined,and the entropy weight method is used to weight these features to reduce the interference of insensitive features.Finally,the attention mechanism is introduced to improve the dual-channel CNN,which is used to adaptively fuse the weighted multi-dimensional feature sets of heterogeneous sensors,to flexibly select heterogeneous sensor information so as to achieve an accurate diagnosis.Experimental results show that the weighted multi-dimensional feature set obtained by the proposed method has a high fault-representation ability and low information redundancy.It can diagnose simultaneously internal wear faults of the hydraulic directional valve and electromagnetic faults of actuators that are difficult to diagnose by traditional methods.This proposed method can achieve high fault-diagnosis accuracy under severe working conditions.展开更多
In this article, we get non-selfsimilar elementary waves of the conservation laws in another kind of view, which is different from the usual self-similar transformation. The solution has different global structure. Th...In this article, we get non-selfsimilar elementary waves of the conservation laws in another kind of view, which is different from the usual self-similar transformation. The solution has different global structure. This article is divided into three parts. The first part is introduction. In the second part, we discuss non-selfsimilar elementary waves and their interactions of a class of twodimensional conservation laws. In this case, we consider the case that the initial discontinuity is parabola with u＋ 〉 0, while explicit non-selfsirnilar rarefaction wave can be obtained. In the second part, we consider the solution structure of case u＋ 〈 0. The new solution structures are obtained by the interactions between different elementary waves, and will continue to interact with other states. Global solutions would be very different from the situation of one dimension.展开更多
文摘The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed out from such logic system. This article aims to rearticulate the underlying lucid multi-dimensional logic system, which faded in obscurity only because of time-out loss of the mid-right concept. Retracing this past tacit but important concept could uncover a multi-dimensional system over a point relating to all matters while capturing the central core of the matter. The seemingly unmanageable multidimensional logic was strengthened by verification processes which affirmed its further extensions, and made up the language of the people, the concepts of yin-yang(阴阳), and the development of extensions of Ba Gua(八卦) derivatives, which furthered the interpretation of the space-time properties and Chinese medicine.
基金the financial support from the Guangxi Natural Science Foundation(grant no.2021GXNSFDA075012,2023GXNSFGA026002)National Natural Science Foundation of China(52104298,22075073,52362027,52462029)Fundamental Research Funds for the Central Universities(531107051077).
文摘Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial for acquiring stable NiSe2-based materials for sodium-ion batteries(SIBs),Herein,a stress dissipation strategy driven by architecture engineering is proposed,which can achieve ultrafast and ultralong sodium storage properties.Different from the conventional sphere-like or rod-like architecture,the three-dimensional(3D)flower-like NiSe_(2)@C composite is delicately designed and assembled with onedimensional nanorods and carbon framework.More importantly,the fundamental mechanism of improved structure stability is unveiled by simulations and experimental results simultaneously.It demonstrates that this designed multidimensional flower-like architecture with dispersed nanorods can balance the structural mismatch,avoid concentrated local strain,and relax the internal stress,mainly induced by the unavoidable volume variation during the repeated conversion processes.Moreover,it can provide more Na^(+)-storage sites and multi-directional migration pathways,leading to a fast Na^(+)-migration channel with boosted reaction kinetic.As expected,it delivers superior rate performance(441 mA h g^(-1)at 5.0 A g^(-1))and long cycling stability(563 mA h g^(-1)at 1.0 A g^(-1)over 1000 cycles)for SIBs.This work provides useful insights for designing high-performance conversion-based anode materials for SIBs.
文摘This paper explores whole-process engineering consulting,including its application models in public buildings and elderly-friendly projects,such as service integration and whole lifecycle management.It also addresses the construction of multi-dimensional collaborative theoretical models,public space streamline organization,and other aspects,emphasizing the importance of multi-dimensional collaboration.Additionally,it highlights the role of talent cultivation and digital transformation in enhancing project efficiency.
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co-supported by the National Key R&D Program of China(No.2023YFB4704400)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F030012)the National Natural Science Foundation of China General Project(No.62373033)。
文摘A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.
基金Sponsored by the Quality Engineering Project of Education Department of Anhui Province(2022jyxm671)Research Team Project of Anhui Xinhua University(kytd202202)+1 种基金Key Project of Scientific Research(Natural Science)of Higher Education Institutions in Anhui Province(2022AH051861)Teaching Reform Research and Practice Quality Engineering Project of Anhui Xinhua University(2024jy035).
文摘During the critical transformation period of landscape architecture major after the adjustment of disciplinary structure and the changes in market demand,private colleges and universities,as important places for cultivating local talents,have pain points such as uneven quality of teachers and students and weak innovation and practice.The practice system with“multi-dimensional Integration”integrates four dimensions:interdisciplinary integration,spatial and temporal intersection,historical inheritance,and behavioral activity,deepens the disciplinary connotation,and integrates the three elements of nature,humanity,and technology,aiming to provide a new path for private colleges and universities to cultivate application-oriented and compound talents with innovative capabilities.In terms of optimizing talent cultivation and adapting to industry changes,this system provides thinking and reference for landscape architecture major,helping the major reshape its core competitiveness and promoting educational innovation and industry development.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
基金supported by the National Key R&D Program of China(No.2021YFC2103600)the National Natural Science Foundation of China(Nos.21878156,21978131,22275085,and 22278224)+2 种基金the Natural Science Foundation of Jiangsu Province(Nos.BK20200089 and BK20200691)the Project of Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the State Key Laboratory of Materials-Oriented Chemical Engineering(No.KL21-08).
文摘Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)featured chromophore(HBT-DPI)that shows flexible emission tunability via the multidimensional regulation of intra-and intermolecular H-bonds.The feature of switchable intramolecular Hbonds is induced via incorporating several hydrogen bond acceptors and donors into one single HBT-DPI molecule,allowing the“turn on/off”of ESIPT process by forming isomers with distinct intramolecular Hbonds configurations.In response to different external H-bonding environments,the obtained four types of crystal/cocrystals vary in the contents of isomers and the molecular packing modes,which are mainly guided by the intermolecular H-bonds,exhibiting non-emissive features or emissions ranging from green to orange.Utilizing the feature of intermolecular H-bond guided molecular packing,we demonstrate the utility of this fluorescent material for visualizing hydrophobic/hydrophilic areas on large-scale heterogeneous surfaces of modified poly(1,1-difluoroethylene)(PVDF)membranes and quantitatively estimating the surface hydrophobicity,providing a new approach for hydrophobicity/hydrophilicity monitoring and measurement.Overall,this study represents a new design strategy for constructing multi-dimensional hydrogen bond regulated ESIPT-based fluorescent materials that enable multiple emissions and unique applications.
基金Project(2023JH26-10100002)supported by the Liaoning Science and Technology Major Project,ChinaProjects(U21A20117,52074085)supported by the National Natural Science Foundation of China+1 种基金Project(2022JH2/101300008)supported by the Liaoning Applied Basic Research Program Project,ChinaProject(22567612H)supported by the Hebei Provincial Key Laboratory Performance Subsidy Project,China。
文摘Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
文摘The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends on a deep understanding of customer behavior. This study proposes a theoretical framework for multi-dimensional customer behavior analysis, aiming to comprehensively capture customer behavioral characteristics in the digital environment. This framework integrates concepts of multi-source data including transaction history, browsing trajectories, social media interactions, and location information, constructing a theoretically more comprehensive customer profile. The research discusses the potential applications of this theoretical framework in precision marketing scenarios such as personalized recommendations, cross-selling, and customer churn prevention. Through analysis, the study points out that multi-dimensional analysis may significantly improve the targeting and theoretical conversion rates of marketing activities. However, the research also explores theoretical challenges that may be faced in the application process, such as data privacy and information overload, and proposes corresponding conceptual coping strategies. This study provides a new theoretical perspective on how businesses can optimize marketing decisions using big data thinking while respecting customer privacy, laying a foundation for future empirical research.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
文摘The study constructed a multi-dimensional feedback mode integrating teacher feedback, peer feedback and network feedback, and applied it in the teaching of College English Writing. After 16 weeks of teaching, the students in the multi-dimen-sional feedback class had significantly better overall writing scores than those in the teacher-feedback class. In terms of individual scores, multi-dimensional feedback played a better role in improving vocabulary and grammar than the class using teacher feed-back. However, there were no significant differences in the responses of writing tasks, coherence and cohesion. The study showed that most students were satisfied with the mode, believing that it was helpful to relieve writing anxiety, stimulate writing interest and improve their writing level.
基金This work was financially supported by the National Natural Science Foundation of China(Nos.51972039,51803018,and 51661145025)LiaoNing Revitalization Talents Program(No.XLYC1902122).
文摘Recently,multilevel structural carbon aerogels are deemed as attractive candidates for microwave absorbing materials.Nevertheless,excessive stack and agglomeration for low-dimension carbon nanomaterials inducing impedance mismatch are significant challenges.Herein,the delicate“3D helix-2D sheet-1D fiber-0D dot”hierarchical aerogels have been successfully synthesized,for the first time,by sequential processes of hydrothermal self-assembly and in-situ chemical vapor deposition method.Particularly,the graphene sheets are uniformly intercalated by 3D helical carbon nanocoils,which give a feasible solution to the mentioned problem and endows the as-obtained aerogel with abundant porous structures and better dielectric properties.Moreover,by adjusting the content of 0D core-shell structured particles and the parameters for growth of the 1D carbon nanofibers,tunable electromagnetic properties and excellent impedance matching are achieved,which plays a vital role in the microwave absorption performance.As expected,the optimized aerogels harvest excellent performance,including broad effective bandwidth and strong reflection loss at low filling ratio and thin thickness.This work gives valuable guidance and inspiration for the design of hierarchical materials comprised of dimensional gradient structures,which holds great application potential for electromagnetic wave attenuation.
基金National Natural Science Foundation of China Under Award Number 50878184National High Technology Research and Development Program (863 Program) of China Under Grant No. 2006AA04Z437Graduate Starting Seed Fund of Northwestern Polytechnical University Under the Grant No. Z2012059
文摘Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility that considers multi-dimensional performance limit state parameters and makes a first attempt to develop fragility curves for a multi-span continuous (MSC) concrete girder bridge considering two performance limit state parameters: column ductility and transverse deformation in the abutments. The main purpose of this paper is to show that the performance limit states, which are compared with the seismic response parameters in the calculation of fragility, should be properly modeled as randomly interdependent variables instead of deterministic quantities. The sensitivity of fragility curves is also investigated when the dependency between the limit states is different. The results indicate that the proposed method can be used to describe the vulnerable behavior of bridges which are sensitive to multiple response parameters and that the fragility information generated by this method will be more reliable and likely to be implemented into transportation network loss estimation.
基金the National Key Research&Development Program of China(2016YFB020071)the National Natural Science Foundation of China(Grants 11532016 and 11702315).
文摘The simulation of hypersonic flows with fully unstructured(tetrahedral)grids has severe problems with respect to the prediction of stagnation region heating,due to the random face orientation without alignment to the bow shock.To improve the accuracy of aero-heating predictions,three multi-dimensional approaches on unstructured grids are coupled in our Reynolds-averaged Navier-Stokes(RANS)solver,including multi-dimensional upwind flux reconstruction(MUP),multi-dimensional limiter(MLP-u2)and multi-dimensional gradient reconstruction(MLR).The coupled multi-dimensional RANS solver is validated by several typical verification and validation(V&V)cases,including hypersonic flows over a cylinder,a blunt biconic,and a double-ellipsoid,with commonly used prism/tetrahedral hybrid grids.Finally,the coupled multi-dimensional solver is applied to simulating the heat flux distribution over a 3D engineering configuration,i.e.a Hermes-like space shuttle model.The obtained numerical results are compared with experimental data.The predicted results demonstrate that the coupled multi-dimensional approach has a good prediction capability on aerodynamic heating over a wide range of complex engineering configurations.
基金supported by the National Natural Science Foundation of China(Nos.51805376 and U1709208)the Zhejiang Provincial Natural Science Foundation of China(Nos.LY20E050028 and LD21E050001)。
文摘Because the hydraulic directional valve usually works in a bad working environment and is disturbed by multi-factor noise,the traditional single sensor monitoring technology is difficult to use for an accurate diagnosis of it.Therefore,a fault diagnosis method based on multi-sensor information fusion is proposed in this paper to reduce the inaccuracy and uncertainty of traditional single sensor information diagnosis technology and to realize accurate monitoring for the location or diagnosis of early faults in such valves in noisy environments.Firstly,the statistical features of signals collected by the multi-sensor are extracted and the depth features are obtained by a convolutional neural network(CNN)to form a complete and stable multi-dimensional feature set.Secondly,to obtain a weighted multi-dimensional feature set,the multi-dimensional feature sets of similar sensors are combined,and the entropy weight method is used to weight these features to reduce the interference of insensitive features.Finally,the attention mechanism is introduced to improve the dual-channel CNN,which is used to adaptively fuse the weighted multi-dimensional feature sets of heterogeneous sensors,to flexibly select heterogeneous sensor information so as to achieve an accurate diagnosis.Experimental results show that the weighted multi-dimensional feature set obtained by the proposed method has a high fault-representation ability and low information redundancy.It can diagnose simultaneously internal wear faults of the hydraulic directional valve and electromagnetic faults of actuators that are difficult to diagnose by traditional methods.This proposed method can achieve high fault-diagnosis accuracy under severe working conditions.
基金Sponsored by the National Natural Science Foundation of China (10671116,10871199, and 10001023)Hou Yingdong Fellowship (81004), The China Scholarship Council, Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, Natural Science Foundation of Guangdong (06027210 and 000804)Natural Science Foundation of Guangdong Education Bureau (200030)
文摘In this article, we get non-selfsimilar elementary waves of the conservation laws in another kind of view, which is different from the usual self-similar transformation. The solution has different global structure. This article is divided into three parts. The first part is introduction. In the second part, we discuss non-selfsimilar elementary waves and their interactions of a class of twodimensional conservation laws. In this case, we consider the case that the initial discontinuity is parabola with u＋ 〉 0, while explicit non-selfsirnilar rarefaction wave can be obtained. In the second part, we consider the solution structure of case u＋ 〈 0. The new solution structures are obtained by the interactions between different elementary waves, and will continue to interact with other states. Global solutions would be very different from the situation of one dimension.
