Flavonoids in plants is very important in its ecological role and economicvalue. The dynamic features of flavonoids content in different organs of larch (Larix gmelinii) atdifferent light and temperature conditions we...Flavonoids in plants is very important in its ecological role and economicvalue. The dynamic features of flavonoids content in different organs of larch (Larix gmelinii) atdifferent light and temperature conditions were investigated in this study. Results showed that theorder of flavonoids content in different organs from high to low was 7.78% (stem bark) > 2.79%(leaves) > 1.72% (branches) > 1.19% (stem xylem)and different organs had a great seasonal variationin flavonoids content, but the change of flavonoids content at different temperature was not obviousin different organs., The content of flavonoids in barck had, a positive correlation withtemperature (R^2=0.75), but that in other organs had slight variation with the change oftemperatures. For all the tested organs, the flavonoids content in summer and autumn wasapproximately 3-4 times higher than in spring and winter. This is attributed to the great stressfrom environmental physical variables such as UV radiation, high temperature that induce theaccumulation of flavonoids. The flavonoid content of sun leaves was evidently higher than that ofshade leaves, and leaves at upper part of canopy had a higher flavonoids content compared with thatat other parts. This result indicates that sun radiation could improve flavonoids production inleaves (R^2=0.76). The flavonoids may actively evolve in plant defenses to environmental stress,protecting larch from the damage of high temperature and radiation, and its main function isdifferent in different organs.展开更多
Urban transportation systems are facing severe challenges due to the rapid growth of the urban population,especially in China.Suspended monorail system(SMS),as a sky rail transportation form,can effectively alleviate ...Urban transportation systems are facing severe challenges due to the rapid growth of the urban population,especially in China.Suspended monorail system(SMS),as a sky rail transportation form,can effectively alleviate urban traffic congestion due to its independent right-of-way and minimal ground footprint.However,the SMS possesses a special traveling system with unique vehicle structure and bridge configuration,which results in significant differences in both the mechanisms and dynamics problems associated with train–bridge interaction(TBI)when contrasted with those of traditional railway systems.Therefore,a thorough understanding of the SMS dynamics is essential for ensuring the operational safety of the system.This article presents a state-of-the-art review of the TBI modeling methodologies,critical dynamic features,field tests,and practice of the SMS in China.Firstly,the development history,technical features,and potential dynamics problems of the SMS are briefly described,followed by the mechanical characteristics and mechanisms of the train–bridge interactive systems.Then,the modeling methodology of the fundamental elements in the suspended monorail TBI is systematically reviewed,including the suspended train subsystem,bridge subsystem,train–bridge interaction relationships,system excitations,and solution method.Further,the typical dynamic features of the TBI under various operational scenarios are elaborated,including different train speeds,a variety of line sections,and a natural wind environment.Finally,the first new energy-based SMS test line in the world is systematically introduced,including the composition and functionality of the system,the details of the conducted field tests,and the measured results of the typical dynamic responses.At the end of the paper,both the guidance on further improvement of the SMS and future research topics are proposed.展开更多
This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data a...This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.展开更多
The E_(s) layer is a thin layer that concentrates metallic ions in the mesosphere and lower thermosphere(MLT)region.When it occurs,it can affect the performance of the Global Navigation Satellite System and high/very ...The E_(s) layer is a thin layer that concentrates metallic ions in the mesosphere and lower thermosphere(MLT)region.When it occurs,it can affect the performance of the Global Navigation Satellite System and high/very high frequency(HF/VHF)radio communications.Previous studies mainly focused on the one-dimensional structure of E_(s) layer in the vertical direction.However,due to the limitation of observations,the horizontal structure of E_(s) layers is not yet fully understood.This study investigated the horizontal structure of E_(s) layers using amateur radio data in the European sector during the summer of 2020.Statistical analysis shows that the horizontal structure of E_(s) layer is mainly elongated in the east-west direction.In addition,we investigated the dynamics of the E_(s) layers,which primarily propagates in the northeast-southwest direction with a speed of 50-200 m/s.The results provide us a way for obtaining the horizontal structure and dynamic features of E_(s) layers,which can help improve our understanding of the formation and evolution of E_(s) layers.展开更多
Introduction The molecular dynamics simulation technique has recently proved to be a suitable alternative approachfor simulation of vibrational spectroscopy. In this study, molecular dynamics was utilized to understan...Introduction The molecular dynamics simulation technique has recently proved to be a suitable alternative approachfor simulation of vibrational spectroscopy. In this study, molecular dynamics was utilized to understandlow frequency vibrations in highly ordered poly(ρ-phenylene terephthalmide) (PPTA). A key structuralfeature of this polymer is the presence of hydrogen bonds. There is little question that this strong localized展开更多
The groundwater level of 39 observation wells including 35 unconfined wells and 4 confined wells from 2004 to 2006 in North China Plain(NCP) was monitored using automatic groundwater monitoring data loggers KADEC-MIZU...The groundwater level of 39 observation wells including 35 unconfined wells and 4 confined wells from 2004 to 2006 in North China Plain(NCP) was monitored using automatic groundwater monitoring data loggers KADEC-MIZU II of Japan.The automatic groundwater sensors were installed for the corporation project between China and Japan.Combined with the monitoring results from 2004 to 2006 with the major factors affecting the dynamic patterns of groundwater, such as topography and landform, depth of groundwater level, exploitation or discharge extent, rivers and lakes, the dynamic regions of NCP groundwater were gotten.According to the dynamic features of groundwater in NCP, six dynamic patterns of groundwater level were identified, including discharge pattern in the piedmont plain, lateral recharge-runoff-discharge pattern in the piedmont plain, recharge-discharge pattern in the central channel zone, precipitation infiltration-evaporation pattern in the shallow groundwater region of the central plain, lateral recharge-evaporation pattern in the recharge-affected area along the Yellow River and infiltration-discharge-evaporation pattern in the littoral plain.Based on this, the groundwater fluctuation features of various dynamic patterns were interpreted and the influencing factors of different dynamic patterns were compared.展开更多
Detailed parametric study of three-dimensional gas-particle multiphase flow characteristics in U-beam tube bundle inertial separators was conducted by numerical simulation. The carrier phase was treated in the Euleria...Detailed parametric study of three-dimensional gas-particle multiphase flow characteristics in U-beam tube bundle inertial separators was conducted by numerical simulation. The carrier phase was treated in the Eulerian frame, the particles were tracked in the Lagrangian frame, and particle-wall collision was considered. Simulation carried out at different inflow rate and mass loading ratios revealed the pressure losses in the separators, velocity field of the gas phase, and the trajectories of particles. The study results revealed the multiphase flow-dynamic features of the separators, and the relationship between separator pressure losses and different inlet velocity. The numerical simulation can provide basis both for optimal design of impacting-inertial separator used in circulating fluidized bed boiler; and for study of gas-particle multiphase circumfluence flow.展开更多
Short-term voltage stability(STVS)assessment is a critical monitoring technology in modern power systems.During daily operation,transmission lines may switch on or off due to scheduled maintenance or unexpected faults...Short-term voltage stability(STVS)assessment is a critical monitoring technology in modern power systems.During daily operation,transmission lines may switch on or off due to scheduled maintenance or unexpected faults,which poses challenges to the STVS assessment under varying topology change conditions.To adapt the STVS assessment to the system topology changes,we propose a deep-learning-based STVS assessment model with the topology-adaptive voltage dynamic feature and the fine-tuning domain transfer for power systems with changing system topologies.The topology-adaptive voltage dynamic feature,extracted from streaming time-series data of phasor measurement units(PMUs),is used to characterize transient voltage stability.The voltage dynamic features depend on the balance of reactive power flow and system topology,effectively revealing both spatio-temporal patterns of post-disturbance system dynamics.The simulation results based on large disturbances in the New England 39-bus power system demonstrate that the proposed model achieves superior STVS assessment performance,with an accuracy of 99.65%in predicting voltage stability compared with the existing deep learning methods.The proposed model also performs well when applied to the larger IEEE 145-bus power system.The fine-tuning domain transfer of the proposed model adapts very well to system topology changes in power systems.It achieves an accuracy of 99.50%in predicting the STVS for the New England 39-bus power system with the transmission line alternation.Furthermore,the proposed model demonstrates strong robustness to noisy and missing data.展开更多
For the issue of low positioning accuracy in dynamic environments with traditional simultaneous localisation and mapping(SLAM),a dynamic point removal strategy combining object detection and optical flow tracking has ...For the issue of low positioning accuracy in dynamic environments with traditional simultaneous localisation and mapping(SLAM),a dynamic point removal strategy combining object detection and optical flow tracking has been proposed.To fully utilise the semantic information,an ellipsoid model of the detected semantic objects was first constructed based on the plane and point cloud constraints,which assists in loop closure detection.Bilateral semantic map matching was achieved through the Kuhn-Munkres(KM)algorithm maximum weight assignment,and the pose transformation between local and global maps was determined by the random sample consensus(RANSAC)algorithm.Finally,a stable semantic SLAM system suitable for dy-namic environments was constructed.The effectiveness of achieving the system's positioning accuracy under dynamic inter-ference and large visual-inertial loop closure was verified by the experiment.展开更多
Epilepsy often accompanies cognitive impairments,which are featured by dynamics of EEG data.The eigenmode method,combined with functional networks derived from EEG data,provides a valid method to investigate dynamical...Epilepsy often accompanies cognitive impairments,which are featured by dynamics of EEG data.The eigenmode method,combined with functional networks derived from EEG data,provides a valid method to investigate dynamical characteristics of the brain’s integration and segregation while establishing connections with cognitive function.Based on the transfer entropy method,we utilize the eigenmode approach to analyze SEEG data from epilepsy patients,which extends the theory of eigenmode hierarchical modules to directed functional networks.This work mainly refines and employs the dynamical characteristics from the eigenmodes of the epilepsy directional functional networks,including integration and segregation theories and proposes the network’s functional recombination rate feature.Results indicate that directed functional networks constructed through transfer entropy can also manifest the phenomenon of hierarchical modules in brain functional modes.In addition,during epileptic seizures,higher layers of overall integration features and increased functional recombination rates are observed.Furthermore,alterations in the aggregation of prominent nodes within the eigenmodes of epilepsy patients are noted during seizure episodes.This paper provides an improved method for the analysis of dynamical features of directed epilepsy network,which may potentially provide help and new understanding for the analysis of functional features of epilepsy.展开更多
Stability is the key issue for kinetic-energy supercavitating projectiles.Our previous work established a six degrees of freedom(DOF)dynamic model for supercavitating projectiles.However,the projectile’s structure di...Stability is the key issue for kinetic-energy supercavitating projectiles.Our previous work established a six degrees of freedom(DOF)dynamic model for supercavitating projectiles.However,the projectile’s structure did not meet our current design specifications(its sailing distance could reach 100 m at an initial speed of 500 m/s).The emphasis of this study lies in optimizing the projectile’s configuration.Therefore,a program was developed to optimize the projectile’s structure to achieve an optimal design or the largest sailing distance.The program is a working optimal method based on the genetic algorithm(GA).Additionally,the convergence standard and population producing strategy were improved,which greatly elevated the calculation speed and precision.To meet design specifications,the improved GA was combined with the 6DOF model,which establishes a dynamic optimization problem.The new projectile’s structure was obtained by solving this problem.Then,the new structures’dynamic features were compared with the ideals proposed in this paper.The criterion of stability,which is called weakened self-stability,was redefined based on the results.The weakened self-stability is the optimal stability for an actual kinetic projectile motion,and it is instructive for the design of supercavitating projectiles in the future.展开更多
The present paper deals with the Sharma-Tasso-Olver-Burgers equation(STOBE)and its conservation laws and kink solitons.More precisely,the formal Lagrangian,Lie symmetries,and adjoint equations of the STOBE are firstly...The present paper deals with the Sharma-Tasso-Olver-Burgers equation(STOBE)and its conservation laws and kink solitons.More precisely,the formal Lagrangian,Lie symmetries,and adjoint equations of the STOBE are firstly constructed to retrieve its conservation laws.Kink solitons of the STOBE are then extracted through adopting a series of newly well-designed approaches such as Kudryashov and exponential methods.Diverse graphs in 2 and 3D postures are formally portrayed to reveal the dynamical features of kink solitons.According to the authors’knowledge,the outcomes of the current investigation are new and have been listed for the first time.展开更多
The topic recognition for dynamic topic number can realize the dynamic update of super parameters,and obtain the probability distribution of dynamic topics in time dimension,which helps to clear the understanding and ...The topic recognition for dynamic topic number can realize the dynamic update of super parameters,and obtain the probability distribution of dynamic topics in time dimension,which helps to clear the understanding and tracking of convection text data.However,the current topic recognition model tends to be based on a fixed number of topics K and lacks multi-granularity analysis of subject knowledge.Therefore,it is impossible to deeply perceive the dynamic change of the topic in the time series.By introducing a novel approach on the basis of Infinite Latent Dirichlet allocation model,a topic feature lattice under the dynamic topic number is constructed.In the model,documents,topics and vocabularies are jointly modeled to generate two probability distribution matrices:Documentstopics and topic-feature words.Afterwards,the association intensity is computed between the topic and its feature vocabulary to establish the topic formal context matrix.Finally,the topic feature is induced according to the formal concept analysis(FCA)theory.The topic feature lattice under dynamic topic number(TFL DTN)model is validated on the real dataset by comparing with the mainstream methods.Experiments show that this model is more in line with actual needs,and achieves better results in semi-automatic modeling of topic visualization analysis.展开更多
Remote passive drone detection in the presence of strong background noise is challenging,since they are point objects and cannot be recognized by their contour detection.In this study,we introduce a new passive single...Remote passive drone detection in the presence of strong background noise is challenging,since they are point objects and cannot be recognized by their contour detection.In this study,we introduce a new passive single-photon dynamic imaging method using quantum compressed sensing.This method utilizes the inherent randomness of photon radiation and detection to construct a compressive imaging system.It captures the broadband dynamic features of the point object through sparse photon detection,achieving a detectable bandwidth up to 2.05 GHz,which is significantly higher than current photon-counting imaging techniques.The method also shows excellent noise resistance,achieving high-quality imaging with a signal-to-background ratio of 1/332.This technique significantly enhances the use of single-photon imaging in real-world applications.展开更多
Recognizing emotions from speech is of great significance in enhancing human-machine interaction.Convolutional neural networks(CNN)continuously compress size and stack weighted values when capturing temporal dynamic f...Recognizing emotions from speech is of great significance in enhancing human-machine interaction.Convolutional neural networks(CNN)continuously compress size and stack weighted values when capturing temporal dynamic features,resulting in the loss of important dynamic features in different channels and depths during the extraction process,which reduces recognition accuracy.To address this issue,the U-Net architecture is employed in this study for speech emotion recognition,and an extended version of the U-Net structure is proposed.The specific method involves extracting the temporal dynamic features of the audio signal through rectangular convolution to generate the Mel-spectrogram dynamic feature map.Then,the U-Net architecture is utilized to establish connections between feature maps of varying scales,while channel selection attention is employed to assess dissimilarities among dynamic features across different channels.Experimental findings on the combined CER dataset reveal that the enhanced U-Net effectively filters essential temporal dynamic features,resulting in a 4.29 percentage point improvement in recognition accuracy compared to the baseline model.展开更多
Detection and counting of abalones is one of key technologies of abalones breeding density estimation.The abalones in the breeding stage are small in size,densely distributed,and occluded between individuals,so the ex...Detection and counting of abalones is one of key technologies of abalones breeding density estimation.The abalones in the breeding stage are small in size,densely distributed,and occluded between individuals,so the existing object detection algorithms have low precision for detecting the abalones in the breeding stage.To solve this problem,a detection and counting method of juvenile abalones based on improved SSD network is proposed in this research.The innovation points of this method are:Firstly,the multi-layer feature dynamic fusion method is proposed to obtain more color and texture information and improve detection precision of juvenile abalones with small size;secondly,the multiscale attention feature extraction method is proposed to highlight shape and edge feature information of juvenile abalones and increase detection precision of juvenile abalones with dense distribution and individual coverage;finally,the loss feedback training method is used to increase the diversity of data and the pixels of juvenile abalones in the images to get the even higher detection precision of juvenile abalones with small size.The experimental results show that the AP@0.5 value,AP@0.7 value and AP@0.75 value of the detection results of the proposed method are 91.14%,89.90% and 80.14%,respectively.The precision and recall rates of the counting results are 99.59% and 97.74%,respectively,which are superior to the counting results of SSD,FSSD,MutualGuide,EfficientDet and VarifocalNet models.The proposed method can provide support for real-time monitoring of aquaculture density for juvenile abalones.展开更多
Investigated in the present paper is a fifth-order nonlinear evolution(FONLE)equation,known as a nonlinear water wave(NLWW)equation,with applications in the applied sciences.More precisely,a traveling wave hypothesis ...Investigated in the present paper is a fifth-order nonlinear evolution(FONLE)equation,known as a nonlinear water wave(NLWW)equation,with applications in the applied sciences.More precisely,a traveling wave hypothesis is firstly applied that reduces the FONLE equation to a 1D domain.The Kudryashov methods(KMs)are then adopted as leading techniques to construct specific wave structures of the governing model which are classified as W-shaped and other solitons.In the end,the effect of changing the coefficients of nonlinear terms on the dynamical features of W-shaped and other solitons is investigated in detail for diverse groups of the involved parameters.展开更多
基金This paper is supported by the National Natural Science Foundation of China (30300271) and the Key Project of Chinese Ministry of Education (104191).
文摘Flavonoids in plants is very important in its ecological role and economicvalue. The dynamic features of flavonoids content in different organs of larch (Larix gmelinii) atdifferent light and temperature conditions were investigated in this study. Results showed that theorder of flavonoids content in different organs from high to low was 7.78% (stem bark) > 2.79%(leaves) > 1.72% (branches) > 1.19% (stem xylem)and different organs had a great seasonal variationin flavonoids content, but the change of flavonoids content at different temperature was not obviousin different organs., The content of flavonoids in barck had, a positive correlation withtemperature (R^2=0.75), but that in other organs had slight variation with the change oftemperatures. For all the tested organs, the flavonoids content in summer and autumn wasapproximately 3-4 times higher than in spring and winter. This is attributed to the great stressfrom environmental physical variables such as UV radiation, high temperature that induce theaccumulation of flavonoids. The flavonoid content of sun leaves was evidently higher than that ofshade leaves, and leaves at upper part of canopy had a higher flavonoids content compared with thatat other parts. This result indicates that sun radiation could improve flavonoids production inleaves (R^2=0.76). The flavonoids may actively evolve in plant defenses to environmental stress,protecting larch from the damage of high temperature and radiation, and its main function isdifferent in different organs.
基金supported by the National Natural Science Foundation of China(Grant Nos.52202483,52108476,and 52388102)。
文摘Urban transportation systems are facing severe challenges due to the rapid growth of the urban population,especially in China.Suspended monorail system(SMS),as a sky rail transportation form,can effectively alleviate urban traffic congestion due to its independent right-of-way and minimal ground footprint.However,the SMS possesses a special traveling system with unique vehicle structure and bridge configuration,which results in significant differences in both the mechanisms and dynamics problems associated with train–bridge interaction(TBI)when contrasted with those of traditional railway systems.Therefore,a thorough understanding of the SMS dynamics is essential for ensuring the operational safety of the system.This article presents a state-of-the-art review of the TBI modeling methodologies,critical dynamic features,field tests,and practice of the SMS in China.Firstly,the development history,technical features,and potential dynamics problems of the SMS are briefly described,followed by the mechanical characteristics and mechanisms of the train–bridge interactive systems.Then,the modeling methodology of the fundamental elements in the suspended monorail TBI is systematically reviewed,including the suspended train subsystem,bridge subsystem,train–bridge interaction relationships,system excitations,and solution method.Further,the typical dynamic features of the TBI under various operational scenarios are elaborated,including different train speeds,a variety of line sections,and a natural wind environment.Finally,the first new energy-based SMS test line in the world is systematically introduced,including the composition and functionality of the system,the details of the conducted field tests,and the measured results of the typical dynamic responses.At the end of the paper,both the guidance on further improvement of the SMS and future research topics are proposed.
基金This work is supported by the Ministry of Education of Humanities and Social Science projects in China(No.20YJCZH124)Guangdong Province Education and Teaching Reform Project No.640:Research on the Teaching Practice and Application of Online Peer Assessment Methods in the Context of Artificial Intelligence.
文摘This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.
基金supported by the National Natural Science Foundation of China(42230207,42104165).
文摘The E_(s) layer is a thin layer that concentrates metallic ions in the mesosphere and lower thermosphere(MLT)region.When it occurs,it can affect the performance of the Global Navigation Satellite System and high/very high frequency(HF/VHF)radio communications.Previous studies mainly focused on the one-dimensional structure of E_(s) layer in the vertical direction.However,due to the limitation of observations,the horizontal structure of E_(s) layers is not yet fully understood.This study investigated the horizontal structure of E_(s) layers using amateur radio data in the European sector during the summer of 2020.Statistical analysis shows that the horizontal structure of E_(s) layer is mainly elongated in the east-west direction.In addition,we investigated the dynamics of the E_(s) layers,which primarily propagates in the northeast-southwest direction with a speed of 50-200 m/s.The results provide us a way for obtaining the horizontal structure and dynamic features of E_(s) layers,which can help improve our understanding of the formation and evolution of E_(s) layers.
文摘Introduction The molecular dynamics simulation technique has recently proved to be a suitable alternative approachfor simulation of vibrational spectroscopy. In this study, molecular dynamics was utilized to understandlow frequency vibrations in highly ordered poly(ρ-phenylene terephthalmide) (PPTA). A key structuralfeature of this polymer is the presence of hydrogen bonds. There is little question that this strong localized
基金National Natural Sciences Foundation of China,No.40671034 No.40830636
文摘The groundwater level of 39 observation wells including 35 unconfined wells and 4 confined wells from 2004 to 2006 in North China Plain(NCP) was monitored using automatic groundwater monitoring data loggers KADEC-MIZU II of Japan.The automatic groundwater sensors were installed for the corporation project between China and Japan.Combined with the monitoring results from 2004 to 2006 with the major factors affecting the dynamic patterns of groundwater, such as topography and landform, depth of groundwater level, exploitation or discharge extent, rivers and lakes, the dynamic regions of NCP groundwater were gotten.According to the dynamic features of groundwater in NCP, six dynamic patterns of groundwater level were identified, including discharge pattern in the piedmont plain, lateral recharge-runoff-discharge pattern in the piedmont plain, recharge-discharge pattern in the central channel zone, precipitation infiltration-evaporation pattern in the shallow groundwater region of the central plain, lateral recharge-evaporation pattern in the recharge-affected area along the Yellow River and infiltration-discharge-evaporation pattern in the littoral plain.Based on this, the groundwater fluctuation features of various dynamic patterns were interpreted and the influencing factors of different dynamic patterns were compared.
文摘Detailed parametric study of three-dimensional gas-particle multiphase flow characteristics in U-beam tube bundle inertial separators was conducted by numerical simulation. The carrier phase was treated in the Eulerian frame, the particles were tracked in the Lagrangian frame, and particle-wall collision was considered. Simulation carried out at different inflow rate and mass loading ratios revealed the pressure losses in the separators, velocity field of the gas phase, and the trajectories of particles. The study results revealed the multiphase flow-dynamic features of the separators, and the relationship between separator pressure losses and different inlet velocity. The numerical simulation can provide basis both for optimal design of impacting-inertial separator used in circulating fluidized bed boiler; and for study of gas-particle multiphase circumfluence flow.
基金supported in part by the National Natural Science Foundation of China(No.21773182)the Fundamental Research Funds for the Central Universities(No.xtr052024009)the HPC Platform,Xi’an Jiaotong University。
文摘Short-term voltage stability(STVS)assessment is a critical monitoring technology in modern power systems.During daily operation,transmission lines may switch on or off due to scheduled maintenance or unexpected faults,which poses challenges to the STVS assessment under varying topology change conditions.To adapt the STVS assessment to the system topology changes,we propose a deep-learning-based STVS assessment model with the topology-adaptive voltage dynamic feature and the fine-tuning domain transfer for power systems with changing system topologies.The topology-adaptive voltage dynamic feature,extracted from streaming time-series data of phasor measurement units(PMUs),is used to characterize transient voltage stability.The voltage dynamic features depend on the balance of reactive power flow and system topology,effectively revealing both spatio-temporal patterns of post-disturbance system dynamics.The simulation results based on large disturbances in the New England 39-bus power system demonstrate that the proposed model achieves superior STVS assessment performance,with an accuracy of 99.65%in predicting voltage stability compared with the existing deep learning methods.The proposed model also performs well when applied to the larger IEEE 145-bus power system.The fine-tuning domain transfer of the proposed model adapts very well to system topology changes in power systems.It achieves an accuracy of 99.50%in predicting the STVS for the New England 39-bus power system with the transmission line alternation.Furthermore,the proposed model demonstrates strong robustness to noisy and missing data.
基金supported in part by the Natural Science Foundation of Shandong Province(No.ZR2024MF036)the National Key Research and Development Plan of China(No.2020AAA0109000)the National Natural Science Foundation of China(Nos.61973184,61803227,61603214,and 61573213).
文摘For the issue of low positioning accuracy in dynamic environments with traditional simultaneous localisation and mapping(SLAM),a dynamic point removal strategy combining object detection and optical flow tracking has been proposed.To fully utilise the semantic information,an ellipsoid model of the detected semantic objects was first constructed based on the plane and point cloud constraints,which assists in loop closure detection.Bilateral semantic map matching was achieved through the Kuhn-Munkres(KM)algorithm maximum weight assignment,and the pose transformation between local and global maps was determined by the random sample consensus(RANSAC)algorithm.Finally,a stable semantic SLAM system suitable for dy-namic environments was constructed.The effectiveness of achieving the system's positioning accuracy under dynamic inter-ference and large visual-inertial loop closure was verified by the experiment.
基金supported by the National Natural Science Foundation of China(Grants Nos.12332004,12202027,12272092,11932003).
文摘Epilepsy often accompanies cognitive impairments,which are featured by dynamics of EEG data.The eigenmode method,combined with functional networks derived from EEG data,provides a valid method to investigate dynamical characteristics of the brain’s integration and segregation while establishing connections with cognitive function.Based on the transfer entropy method,we utilize the eigenmode approach to analyze SEEG data from epilepsy patients,which extends the theory of eigenmode hierarchical modules to directed functional networks.This work mainly refines and employs the dynamical characteristics from the eigenmodes of the epilepsy directional functional networks,including integration and segregation theories and proposes the network’s functional recombination rate feature.Results indicate that directed functional networks constructed through transfer entropy can also manifest the phenomenon of hierarchical modules in brain functional modes.In addition,during epileptic seizures,higher layers of overall integration features and increased functional recombination rates are observed.Furthermore,alterations in the aggregation of prominent nodes within the eigenmodes of epilepsy patients are noted during seizure episodes.This paper provides an improved method for the analysis of dynamical features of directed epilepsy network,which may potentially provide help and new understanding for the analysis of functional features of epilepsy.
基金Supported by the National Natural Science Foundation of China under Grant No.62101590.
文摘Stability is the key issue for kinetic-energy supercavitating projectiles.Our previous work established a six degrees of freedom(DOF)dynamic model for supercavitating projectiles.However,the projectile’s structure did not meet our current design specifications(its sailing distance could reach 100 m at an initial speed of 500 m/s).The emphasis of this study lies in optimizing the projectile’s configuration.Therefore,a program was developed to optimize the projectile’s structure to achieve an optimal design or the largest sailing distance.The program is a working optimal method based on the genetic algorithm(GA).Additionally,the convergence standard and population producing strategy were improved,which greatly elevated the calculation speed and precision.To meet design specifications,the improved GA was combined with the 6DOF model,which establishes a dynamic optimization problem.The new projectile’s structure was obtained by solving this problem.Then,the new structures’dynamic features were compared with the ideals proposed in this paper.The criterion of stability,which is called weakened self-stability,was redefined based on the results.The weakened self-stability is the optimal stability for an actual kinetic projectile motion,and it is instructive for the design of supercavitating projectiles in the future.
文摘The present paper deals with the Sharma-Tasso-Olver-Burgers equation(STOBE)and its conservation laws and kink solitons.More precisely,the formal Lagrangian,Lie symmetries,and adjoint equations of the STOBE are firstly constructed to retrieve its conservation laws.Kink solitons of the STOBE are then extracted through adopting a series of newly well-designed approaches such as Kudryashov and exponential methods.Diverse graphs in 2 and 3D postures are formally portrayed to reveal the dynamical features of kink solitons.According to the authors’knowledge,the outcomes of the current investigation are new and have been listed for the first time.
基金the Key Projects of Social Sciences of Anhui Provincial Department of Education(SK2018A1064,SK2018A1072)the Natural Scientific Project of Anhui Provincial Department of Education(KJ2019A0371)Innovation Team of Health Information Management and Application Research(BYKC201913),BBMC。
文摘The topic recognition for dynamic topic number can realize the dynamic update of super parameters,and obtain the probability distribution of dynamic topics in time dimension,which helps to clear the understanding and tracking of convection text data.However,the current topic recognition model tends to be based on a fixed number of topics K and lacks multi-granularity analysis of subject knowledge.Therefore,it is impossible to deeply perceive the dynamic change of the topic in the time series.By introducing a novel approach on the basis of Infinite Latent Dirichlet allocation model,a topic feature lattice under the dynamic topic number is constructed.In the model,documents,topics and vocabularies are jointly modeled to generate two probability distribution matrices:Documentstopics and topic-feature words.Afterwards,the association intensity is computed between the topic and its feature vocabulary to establish the topic formal context matrix.Finally,the topic feature is induced according to the formal concept analysis(FCA)theory.The topic feature lattice under dynamic topic number(TFL DTN)model is validated on the real dataset by comparing with the mainstream methods.Experiments show that this model is more in line with actual needs,and achieves better results in semi-automatic modeling of topic visualization analysis.
基金supported by Shanxi Province Science and Technology Major Special Project(202201010101005)the Natural Science Foundation of China(U22A2091,62105193,62127817,62075120,62075122,62222509,62205187,6191101445 and 62305200)+4 种基金China Postdoctoral Science Foundation(2022M722006)National Key Research and Development Program of China(2022YFA1404201)Shanxi Province Science and Technology Innovation Talent Team(No.202204051001014)Science and Technology Cooperation Project of Shanxi Province(202104041101021)Shanxi“1331 Project”,111 projects(D18001).
文摘Remote passive drone detection in the presence of strong background noise is challenging,since they are point objects and cannot be recognized by their contour detection.In this study,we introduce a new passive single-photon dynamic imaging method using quantum compressed sensing.This method utilizes the inherent randomness of photon radiation and detection to construct a compressive imaging system.It captures the broadband dynamic features of the point object through sparse photon detection,achieving a detectable bandwidth up to 2.05 GHz,which is significantly higher than current photon-counting imaging techniques.The method also shows excellent noise resistance,achieving high-quality imaging with a signal-to-background ratio of 1/332.This technique significantly enhances the use of single-photon imaging in real-world applications.
基金supported by the Shanghai Science and Technology Commission under Grant No.23010501500.
文摘Recognizing emotions from speech is of great significance in enhancing human-machine interaction.Convolutional neural networks(CNN)continuously compress size and stack weighted values when capturing temporal dynamic features,resulting in the loss of important dynamic features in different channels and depths during the extraction process,which reduces recognition accuracy.To address this issue,the U-Net architecture is employed in this study for speech emotion recognition,and an extended version of the U-Net structure is proposed.The specific method involves extracting the temporal dynamic features of the audio signal through rectangular convolution to generate the Mel-spectrogram dynamic feature map.Then,the U-Net architecture is utilized to establish connections between feature maps of varying scales,while channel selection attention is employed to assess dissimilarities among dynamic features across different channels.Experimental findings on the combined CER dataset reveal that the enhanced U-Net effectively filters essential temporal dynamic features,resulting in a 4.29 percentage point improvement in recognition accuracy compared to the baseline model.
基金jointly supported by the National Key R&D Project(2020YFD0900204)the Yantai Key R&D Project(2019XDHZ084).
文摘Detection and counting of abalones is one of key technologies of abalones breeding density estimation.The abalones in the breeding stage are small in size,densely distributed,and occluded between individuals,so the existing object detection algorithms have low precision for detecting the abalones in the breeding stage.To solve this problem,a detection and counting method of juvenile abalones based on improved SSD network is proposed in this research.The innovation points of this method are:Firstly,the multi-layer feature dynamic fusion method is proposed to obtain more color and texture information and improve detection precision of juvenile abalones with small size;secondly,the multiscale attention feature extraction method is proposed to highlight shape and edge feature information of juvenile abalones and increase detection precision of juvenile abalones with dense distribution and individual coverage;finally,the loss feedback training method is used to increase the diversity of data and the pixels of juvenile abalones in the images to get the even higher detection precision of juvenile abalones with small size.The experimental results show that the AP@0.5 value,AP@0.7 value and AP@0.75 value of the detection results of the proposed method are 91.14%,89.90% and 80.14%,respectively.The precision and recall rates of the counting results are 99.59% and 97.74%,respectively,which are superior to the counting results of SSD,FSSD,MutualGuide,EfficientDet and VarifocalNet models.The proposed method can provide support for real-time monitoring of aquaculture density for juvenile abalones.
文摘Investigated in the present paper is a fifth-order nonlinear evolution(FONLE)equation,known as a nonlinear water wave(NLWW)equation,with applications in the applied sciences.More precisely,a traveling wave hypothesis is firstly applied that reduces the FONLE equation to a 1D domain.The Kudryashov methods(KMs)are then adopted as leading techniques to construct specific wave structures of the governing model which are classified as W-shaped and other solitons.In the end,the effect of changing the coefficients of nonlinear terms on the dynamical features of W-shaped and other solitons is investigated in detail for diverse groups of the involved parameters.
