A heart attack disrupts the normal flow of blood to the heart muscle,potentially causing severe damage or death if not treated promptly.It can lead to long-term health complications,reduce quality of life,and signific...A heart attack disrupts the normal flow of blood to the heart muscle,potentially causing severe damage or death if not treated promptly.It can lead to long-term health complications,reduce quality of life,and significantly impact daily activities and overall well-being.Despite the growing popularity of deep learning,several drawbacks persist,such as complexity and the limitation of single-model learning.In this paper,we introduce a residual learning-based feature fusion technique to achieve high accuracy in differentiating abnormal cardiac rhythms heart sound.Combining MobileNet with DenseNet201 for feature fusion leverages MobileNet lightweight,efficient architecture with DenseNet201,dense connections,resulting in enhanced feature extraction and improved model performance with reduced computational cost.To further enhance the fusion,we employed residual learning to optimize the hierarchical features of heart abnormal sounds during training.The experimental results demonstrate that the proposed fusion method achieved an accuracy of 95.67%on the benchmark PhysioNet-2016 Spectrogram dataset.To further validate the performance,we applied it to the BreakHis dataset with a magnification level of 100X.The results indicate that the model maintains robust performance on the second dataset,achieving an accuracy of 96.55%.it highlights its consistent performance,making it a suitable for various applications.展开更多
This study focuses on determining the second-order irregular wave loads in the time domain without using the Inverse Fast Fourier Transform(IFFT).Considering the substantial displacement effects that Floating Offshore...This study focuses on determining the second-order irregular wave loads in the time domain without using the Inverse Fast Fourier Transform(IFFT).Considering the substantial displacement effects that Floating Offshore Wind Turbine(FOWT)support structures undergo when subjected to wave loads,the time-domain wave method is more suitable,while the frequency-domain method requiring IFFT cannot be used for moving bodies.Nonetheless,the computational challenges posed by the considerable computer time requirements of the time-domain wave method remain a significant obstacle.Thus,the paper incorporates various numerical schemes,including parallel computing and extrapolation of wave forces during specific time steps to improve overall efficiency.Despite the effectiveness of these schemes,the computational difficulties associated with the time-domain wave method persist.This study then proposes an innovative approach utilizing different randomnumbers in distinct segments,significantly reducing the computation of second-order wave loads.This random number interpolation ensures a smooth curve transition between two segments,emphasizingminimizing errors near the end of the first segment.Numerical analyses demonstrate substantial decreases in total computer time for FOWT structural analyses while maintaining consistent steel design results.The proposed method is uncomplicated,requiring only a simple subprogram modification in a conventional wave load computer program.展开更多
Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and ...Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and over-determined problems in the inversion. The correlation complicates the mapping relation between the ATEM data and the earth parameters and thus increases the inversion complexity. To obviate this, we adopt principal component analysis to transform ATEM data into orthogonal principal components （PCs） to reduce the correlations and the data dimensionality and simultaneously suppress the unrelated noise. In this paper, we use an artificial neural network （ANN） to approach the PCs mapping relation with the earth model parameters, avoiding the calculation of Jacobian derivatives. The PC-based ANN algorithm is applied to synthetic data for layered models compared with data-based ANN for airborne time-domain electromagnetic inversion. The results demonstrate the PC-based ANN advantages of simpler network structure, less training steps, and better inversion results over data-based ANN, especially for contaminated data. Furthermore, the PC-based ANN algorithm effectiveness is examined by the inversion of the pseudo 2D model and comparison with data-based ANN and Zhody＇s methods. The results indicate that PC-based ANN inversion can achieve a better agreement with the true model and also proved that PC-based ANN is feasible to invert large ATEM datasets.展开更多
An electromagnetic field is generated through the accelerating movement of two equal but opposite charges of a single dipole. An electromagnetic field can also be generated by a time-varying infinitesimal point charge...An electromagnetic field is generated through the accelerating movement of two equal but opposite charges of a single dipole. An electromagnetic field can also be generated by a time-varying infinitesimal point charge. In this study, a comparison between the electromagnetic fields of an infinitesimal point charge and a dipole has been presented. First, the time-domain potential function of a point source in a 3D conductive medium is derived. Then the electric and magnetic fields in a 3D homogeneous lossless space are derived via the relation between the potential and field. The field differences between the infinitesimal point charge and the dipole in the step-off time, far-source, and near-source zones are analyzed, and the accuracy of the solutions from these sources is investigated. It is also shown that the field of the infinitesimal point charge in the near-source zone is different from that of the dipole, whereas the far-source zone fields of these two sources are identical. The comparison of real and simulated data shows that the infinitesimal point charge represents the real source better than the divole source.展开更多
To effectively minimize the electromagnetic field response in the total field solution, we propose a numerical modeling method for the two-dimensional （2D） time- domain transient electromagnetic secondary field of t...To effectively minimize the electromagnetic field response in the total field solution, we propose a numerical modeling method for the two-dimensional （2D） time- domain transient electromagnetic secondary field of the line source based on the DuFort- Frankel finite-difference method. In the proposed method, we included the treatment of the earth-air boundary conductivity, calculated the normalized partial derivative of the induced electromotive force （Emf）, and determined the forward time step. By extending upward the earth-air interface to the air grid nodes and the zero-value boundary conditions, not only we have a method that is more efficient but also simpler than the total field solution. We computed and analyzed the homogeneous half-space model and the fiat layered model with high precision--the maximum relative error is less than 0.01% between our method and the analytical method--and the solution speed is roughly three times faster than the total-field solution. Lastly, we used the model of a thin body embedded in a homogeneous half-space at different delay times to depict the downward and upward spreading characteristics of the induced eddy current, and the physical interaction processes between the electromagnetic field and the underground low-resistivity body.展开更多
In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this pap...In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this paper,these influences are investigated from the perspective of the time domain.First,a novel time-domain model of the multi-VSC system is obtained by using a multi-scale method.On this basis,a stability criterion is proposed to assess the synchronization stability of the system.Then,the accuracy of the time-domain model and its stability criterion in various conditions are discussed.Moreover,the negative impact of the interaction on the system is quantified.Finally,the above theoretical analysis is also verified in the controller hardware-in-the-loop(CHIL)experiments.展开更多
To address the complex seismic response of long tunnels longitudinally crossing heterogeneous geological formations,this study proposes a three-dimensional SV-wave oblique-incidence input method that accounts for the ...To address the complex seismic response of long tunnels longitudinally crossing heterogeneous geological formations,this study proposes a three-dimensional SV-wave oblique-incidence input method that accounts for the initial disturbance of the wave field induced by geological heterogeneity.The method transforms equivalent twodimensional free-field responses into equivalent nodal forces applied at the boundaries of a 3D numerical model.A longitudinally heterogeneous“hard-soft-hard”site and tunnel system is established,in which the surrounding rock is modeled using the Mohr-Coulomb constitutive law,while the concrete lining is described by the concrete damaged plasticity model.The deformation patterns and failure mechanisms of the site-tunnel system under SV-wave excitation are systematically investigated.The results indicate that seismic damage under SV-wave loading is mainly concentrated in the soft-rock region.Failure of the soft surrounding rock induces pronounced sliding of the overlying hard rock,and the tunnel suffers severe damage due to the combined effects of soft-rock failure and strong ground shaking.Parametric analyses further show that smaller impedance ratios,larger soft-rock widths,and larger incidence angles significantly intensify the seismic response of the tunnel.The findings of this study provide valuable insights for the seismic design of tunnels crossing longitudinally heterogeneous geological formations.展开更多
Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstruc...Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.展开更多
Electrically anisotropic strata are abundant in nature, so their study can help our data interpretation and our understanding of the processes of geodynamics. However, current data processing generally assumes isotrop...Electrically anisotropic strata are abundant in nature, so their study can help our data interpretation and our understanding of the processes of geodynamics. However, current data processing generally assumes isotropic conditions when surveying anisotropic structures, which may cause discrepancies between reality and electromagnetic data interpretation. Moreover, the anisotropic interpretation of the time-domain airborne electromagnetic （TDAEM） method is still confined to one dimensional （1D） cases, and the corresponding three-dimensional （3D） numerical simulations are still in development. In this study, we expanded the 3D TDAEM modeling of arbitrarily anisotropic media. First, through coordinate rotation of isotropic conductivity, we obtained the conductivity tensor of an arbitrary anisotropic rock. Next, we incorporated this into Maxwell＇s equations, using a regular hexahedral grid of vector finite elements to subdivide the solution area. A direct solver software package provided the solution for the sparse linear equations that resulted. Analytical solutions were used to verify the accuracy and feasibility of the algorithm. The proven model was then applied to analyze the effects of arbitrary anisotropy in 3D TDAEM via the distribution of responses and amplitude changes, which revealed that different anisotropy situations strongly affected the responses of TDAEM.展开更多
Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing.This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain anal...Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing.This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis.It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters.First,this study made samples with gradient defects for two types of grouting sleeves,G18 and G20.These included four cases:2D,4D,6D defects(where D is the diameter of the grouting sleeve),and no-defect.Then,an ultrasonic input/output data acquisition system was established.Three-dimensional sound field distribution data were obtained through an orthogonal detection layout and pulse reflection principles.Finally,a novel quantification detection with a comprehensive defect index(DI)was established by comprehensively considering eight feature parameters,such as time-frequency domain Kurtosis factor(KU),Skewness factor(SK),Formfactor(FF),Crest factor(CF),Impulse factor(IF),Clearance factor(CLF),Wavelet packet energy entropy(WPEE),and Hilbert energy peak(HEP).Construct a DI index by quantifying the difference between defect signals and defect free signals in the time-frequency domain.Experimental results show that,under no-defect conditions,the values of feature parameters are significantly lower than those under defect conditions.Among these,the KU,FF,CF,WPEE and HEP exhibit strong correlations with grout sleeve compactness.The proposed DI index in both types of grout sleeves showed good universality with a linear fit goodness of 0.847–0.962.However,G20 the larger inner diameter and length of the sleeve result in a more complex medium effect during ultrasonic propagation,making its DI index more sensitive to defects than the G18 sleeve.Therefore,the presented method is effective for quantitative detection and analysis of the compactness of grouting sleeves.展开更多
文摘A heart attack disrupts the normal flow of blood to the heart muscle,potentially causing severe damage or death if not treated promptly.It can lead to long-term health complications,reduce quality of life,and significantly impact daily activities and overall well-being.Despite the growing popularity of deep learning,several drawbacks persist,such as complexity and the limitation of single-model learning.In this paper,we introduce a residual learning-based feature fusion technique to achieve high accuracy in differentiating abnormal cardiac rhythms heart sound.Combining MobileNet with DenseNet201 for feature fusion leverages MobileNet lightweight,efficient architecture with DenseNet201,dense connections,resulting in enhanced feature extraction and improved model performance with reduced computational cost.To further enhance the fusion,we employed residual learning to optimize the hierarchical features of heart abnormal sounds during training.The experimental results demonstrate that the proposed fusion method achieved an accuracy of 95.67%on the benchmark PhysioNet-2016 Spectrogram dataset.To further validate the performance,we applied it to the BreakHis dataset with a magnification level of 100X.The results indicate that the model maintains robust performance on the second dataset,achieving an accuracy of 96.55%.it highlights its consistent performance,making it a suitable for various applications.
基金funded by National Science and Technology Council,grant number NSTC 113-2223-E-006-014.
文摘This study focuses on determining the second-order irregular wave loads in the time domain without using the Inverse Fast Fourier Transform(IFFT).Considering the substantial displacement effects that Floating Offshore Wind Turbine(FOWT)support structures undergo when subjected to wave loads,the time-domain wave method is more suitable,while the frequency-domain method requiring IFFT cannot be used for moving bodies.Nonetheless,the computational challenges posed by the considerable computer time requirements of the time-domain wave method remain a significant obstacle.Thus,the paper incorporates various numerical schemes,including parallel computing and extrapolation of wave forces during specific time steps to improve overall efficiency.Despite the effectiveness of these schemes,the computational difficulties associated with the time-domain wave method persist.This study then proposes an innovative approach utilizing different randomnumbers in distinct segments,significantly reducing the computation of second-order wave loads.This random number interpolation ensures a smooth curve transition between two segments,emphasizingminimizing errors near the end of the first segment.Numerical analyses demonstrate substantial decreases in total computer time for FOWT structural analyses while maintaining consistent steel design results.The proposed method is uncomplicated,requiring only a simple subprogram modification in a conventional wave load computer program.
基金supported by the National Natural Science Foundation of China (Grant No. 40974039)High-Tech Research and Development Program of China (Grant No.2006AA06205)Leading Strategic Project of Science and Technology, Chinese Academy of Sciences (XDA08020500)
文摘Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and over-determined problems in the inversion. The correlation complicates the mapping relation between the ATEM data and the earth parameters and thus increases the inversion complexity. To obviate this, we adopt principal component analysis to transform ATEM data into orthogonal principal components （PCs） to reduce the correlations and the data dimensionality and simultaneously suppress the unrelated noise. In this paper, we use an artificial neural network （ANN） to approach the PCs mapping relation with the earth model parameters, avoiding the calculation of Jacobian derivatives. The PC-based ANN algorithm is applied to synthetic data for layered models compared with data-based ANN for airborne time-domain electromagnetic inversion. The results demonstrate the PC-based ANN advantages of simpler network structure, less training steps, and better inversion results over data-based ANN, especially for contaminated data. Furthermore, the PC-based ANN algorithm effectiveness is examined by the inversion of the pseudo 2D model and comparison with data-based ANN and Zhody＇s methods. The results indicate that PC-based ANN inversion can achieve a better agreement with the true model and also proved that PC-based ANN is feasible to invert large ATEM datasets.
基金supported by Chinese National Programs for Fundamental Research and Development(No.2012CB416605)the National Natural Science Foundation of China(No.41174090)Development Project of National Key Scientific Equipment(No.ZDYZ2012-1-05-04)
文摘An electromagnetic field is generated through the accelerating movement of two equal but opposite charges of a single dipole. An electromagnetic field can also be generated by a time-varying infinitesimal point charge. In this study, a comparison between the electromagnetic fields of an infinitesimal point charge and a dipole has been presented. First, the time-domain potential function of a point source in a 3D conductive medium is derived. Then the electric and magnetic fields in a 3D homogeneous lossless space are derived via the relation between the potential and field. The field differences between the infinitesimal point charge and the dipole in the step-off time, far-source, and near-source zones are analyzed, and the accuracy of the solutions from these sources is investigated. It is also shown that the field of the infinitesimal point charge in the near-source zone is different from that of the dipole, whereas the far-source zone fields of these two sources are identical. The comparison of real and simulated data shows that the infinitesimal point charge represents the real source better than the divole source.
基金supported by the National High Technology Research and Development Program (863 Program)(2009AA06Z108)
文摘To effectively minimize the electromagnetic field response in the total field solution, we propose a numerical modeling method for the two-dimensional （2D） time- domain transient electromagnetic secondary field of the line source based on the DuFort- Frankel finite-difference method. In the proposed method, we included the treatment of the earth-air boundary conductivity, calculated the normalized partial derivative of the induced electromotive force （Emf）, and determined the forward time step. By extending upward the earth-air interface to the air grid nodes and the zero-value boundary conditions, not only we have a method that is more efficient but also simpler than the total field solution. We computed and analyzed the homogeneous half-space model and the fiat layered model with high precision--the maximum relative error is less than 0.01% between our method and the analytical method--and the solution speed is roughly three times faster than the total-field solution. Lastly, we used the model of a thin body embedded in a homogeneous half-space at different delay times to depict the downward and upward spreading characteristics of the induced eddy current, and the physical interaction processes between the electromagnetic field and the underground low-resistivity body.
基金supported by the Science and Technology Project of State Grid Corporation of China(5400-202199281A-0-0-00).
文摘In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this paper,these influences are investigated from the perspective of the time domain.First,a novel time-domain model of the multi-VSC system is obtained by using a multi-scale method.On this basis,a stability criterion is proposed to assess the synchronization stability of the system.Then,the accuracy of the time-domain model and its stability criterion in various conditions are discussed.Moreover,the negative impact of the interaction on the system is quantified.Finally,the above theoretical analysis is also verified in the controller hardware-in-the-loop(CHIL)experiments.
基金supported by the National Key Research and Development Program(Grant No.2024YFF0508203)the National Natural Science Foundation of China(Grant No.52378475)the Science and Technology Innovation Special Project of Xiongan New Area,National Key R&D Program(Grant No.2025XAGG0056)。
文摘To address the complex seismic response of long tunnels longitudinally crossing heterogeneous geological formations,this study proposes a three-dimensional SV-wave oblique-incidence input method that accounts for the initial disturbance of the wave field induced by geological heterogeneity.The method transforms equivalent twodimensional free-field responses into equivalent nodal forces applied at the boundaries of a 3D numerical model.A longitudinally heterogeneous“hard-soft-hard”site and tunnel system is established,in which the surrounding rock is modeled using the Mohr-Coulomb constitutive law,while the concrete lining is described by the concrete damaged plasticity model.The deformation patterns and failure mechanisms of the site-tunnel system under SV-wave excitation are systematically investigated.The results indicate that seismic damage under SV-wave loading is mainly concentrated in the soft-rock region.Failure of the soft surrounding rock induces pronounced sliding of the overlying hard rock,and the tunnel suffers severe damage due to the combined effects of soft-rock failure and strong ground shaking.Parametric analyses further show that smaller impedance ratios,larger soft-rock widths,and larger incidence angles significantly intensify the seismic response of the tunnel.The findings of this study provide valuable insights for the seismic design of tunnels crossing longitudinally heterogeneous geological formations.
基金funded by the Directorate of Research and Community Service,Directorate General of Research and Development,Ministry of Higher Education,Science and Technologyin accordance with the Implementation Contract for the Operational Assistance Program for State Universities,Research Program Number:109/C3/DT.05.00/PL/2025.
文摘Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.
基金financially supported by National Nonprofit institute Research Grant of IGGE(Nos.AS2017J06,AS2017Y04,and AS2016J10)Survey on coastal area for airborne magnetic method of UNV in Jiangsu(No.DD20160151-03)+3 种基金Key National Research Project of China(No.2017YFC0601900)Key Program of National Natural Science Foundation of China(No.41530320)Natural Science Foundation(No.41274121)China Natural Science Foundation for Young Scientists(No.41404093)
文摘Electrically anisotropic strata are abundant in nature, so their study can help our data interpretation and our understanding of the processes of geodynamics. However, current data processing generally assumes isotropic conditions when surveying anisotropic structures, which may cause discrepancies between reality and electromagnetic data interpretation. Moreover, the anisotropic interpretation of the time-domain airborne electromagnetic （TDAEM） method is still confined to one dimensional （1D） cases, and the corresponding three-dimensional （3D） numerical simulations are still in development. In this study, we expanded the 3D TDAEM modeling of arbitrarily anisotropic media. First, through coordinate rotation of isotropic conductivity, we obtained the conductivity tensor of an arbitrary anisotropic rock. Next, we incorporated this into Maxwell＇s equations, using a regular hexahedral grid of vector finite elements to subdivide the solution area. A direct solver software package provided the solution for the sparse linear equations that resulted. Analytical solutions were used to verify the accuracy and feasibility of the algorithm. The proven model was then applied to analyze the effects of arbitrary anisotropy in 3D TDAEM via the distribution of responses and amplitude changes, which revealed that different anisotropy situations strongly affected the responses of TDAEM.
基金supported in part by the National Natural Science Foundation of China Grant 11962006the Natural Science Foundation of Jiangxi Province of China Grant 20232BAB204067.
文摘Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing.This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis.It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters.First,this study made samples with gradient defects for two types of grouting sleeves,G18 and G20.These included four cases:2D,4D,6D defects(where D is the diameter of the grouting sleeve),and no-defect.Then,an ultrasonic input/output data acquisition system was established.Three-dimensional sound field distribution data were obtained through an orthogonal detection layout and pulse reflection principles.Finally,a novel quantification detection with a comprehensive defect index(DI)was established by comprehensively considering eight feature parameters,such as time-frequency domain Kurtosis factor(KU),Skewness factor(SK),Formfactor(FF),Crest factor(CF),Impulse factor(IF),Clearance factor(CLF),Wavelet packet energy entropy(WPEE),and Hilbert energy peak(HEP).Construct a DI index by quantifying the difference between defect signals and defect free signals in the time-frequency domain.Experimental results show that,under no-defect conditions,the values of feature parameters are significantly lower than those under defect conditions.Among these,the KU,FF,CF,WPEE and HEP exhibit strong correlations with grout sleeve compactness.The proposed DI index in both types of grout sleeves showed good universality with a linear fit goodness of 0.847–0.962.However,G20 the larger inner diameter and length of the sleeve result in a more complex medium effect during ultrasonic propagation,making its DI index more sensitive to defects than the G18 sleeve.Therefore,the presented method is effective for quantitative detection and analysis of the compactness of grouting sleeves.
