A comprehensive acoustical test was conducted in the traditional Ch ine se in-house theater, the theater of Shi`s residence in Tianjin. The measured pa rameters include reverberation time, clarity, lateral reflectance...A comprehensive acoustical test was conducted in the traditional Ch ine se in-house theater, the theater of Shi`s residence in Tianjin. The measured pa rameters include reverberation time, clarity, lateral reflectance and IACC. Prim ary analysis was done with the test result.展开更多
In order to overcome the limitations of traditional microperforated plate with narrow sound absorption bandwidth and a single structure,two multi-cavity composite sound-absorbing materials were designed based on the s...In order to overcome the limitations of traditional microperforated plate with narrow sound absorption bandwidth and a single structure,two multi-cavity composite sound-absorbing materials were designed based on the shape of monoclinic crystals:uniaxial oblique structure(UOS)and biaxial oblique structure(BOS).Through finite element simulation and experimental research,the theoretical models of UOS and BOS were verified,and their sound absorption mechanisms were revealed.At the same time,the influence of multi-cavity composites on sound absorption performance was analyzed based on the theoretical model,and the influence of structural parameters on sound absorption performance was discussed.The research results show that,in the range of 100-2000 Hz,UOS has three sound absorption peaks and BOS has five sound absorption peaks.The frequency range of the half-absorption bandwidth(α>0.5)of UOS and BOS increases by 242% and 229%,respectively.Compared with traditional microperforated sound-absorbing structures,the series and parallel hybrid methods significantly increase the sound-absorbing bandwidth of the sound-absorbing structure.This research has guiding significance for noise control and has broad application prospects in the fields of transportation,construction,and mechanical design.展开更多
Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NV...Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).展开更多
Laser technology holds significant promise for enhancing rock-breaking efficiency.Experimental investigations were carried out on sandstone subjected to laser radiation,aiming to elucidate its response mechanism to su...Laser technology holds significant promise for enhancing rock-breaking efficiency.Experimental investigations were carried out on sandstone subjected to laser radiation,aiming to elucidate its response mechanism to such radiation.The uniaxial compressive strength of sandstone notably decreases by 22.1%–54.7%following exposure to a 750 W laser for 30 s,indicating a substantial weakening effect.Furthermore,the elastic modulus and Poisson ratio of sandstone exhibit an average decrease of 33.7%and 25.9%,respectively.Simultaneously,laser radiation reduces the brittleness of sandstone,increases the dissipated energy proportion,and shifts the failure mode from tensile to tension-shear composite failure.Following laser radiation,both the number and energy of acoustic emission events in the sandstone register a substantial increase,with a more dispersed distribution of these events.In summary,laser radiation induces notable damage to the mechanical properties of sandstone,leading to a substantial decrease in elastic energy storage capacity.Laser rock breaking technology is expected to be applied in hard rock breaking engineering to significantly reduce the difficulty of rock breaking and improve rock breaking efficiency.展开更多
Objective To investigate the value of polar residual network(PResNet)model for assisting evaluation on rat myocardial infarction(MI)segment in myocardial contrast echocardiography(MCE).Methods Twenty-five male SD rats...Objective To investigate the value of polar residual network(PResNet)model for assisting evaluation on rat myocardial infarction(MI)segment in myocardial contrast echocardiography(MCE).Methods Twenty-five male SD rats were randomly divided into MI group(n=15)and sham operation group(n=10).MI models were established in MI group through ligation of the left anterior descending coronary artery using atraumatic suture,while no intervention was given to those in sham operation group after thoracotomy.MCE images of both basal and papillary muscle levels on the short axis section of left ventricles were acquired after 1 week,which were assessed independently by 2 junior and 2 senior ultrasound physicians.The evaluating efficacy of MI segment,the mean interpretation time and the consistency were compared whether under the assistance of PResNet model or not.Results No significant difference of efficacy of evaluation on MI segment was found for senior physicians with or without assistance of PResNet model(both P>0.05).Under the assistance of PResNet model,the efficacy of junior physicians for diagnosing MI segment was significantly improved compared with that without the assistance of PResNet model(both P<0.01),and was comparable to that of senior physicians.Under the assistance of PResNet model,the mean interpretation time of each physician was significantly shorter than that without assistance(all P<0.001),and the consistency between junior physicians and among junior and senior physicians were both moderate(Kappa=0.692,0.542),which became better under the assistance(Kappa=0.763,0.749).Conclusion PResNet could improve the efficacy of junior physicians for evaluation on rat MI segment in MCE images,shorten interpretation time with different aptitudes,also improve the consistency to some extent.展开更多
Effects of ultrasonic vibration(UV)and mechanical vibration(MV)on the Mn-rich phase modification and mechanical properties of Al−12Si−4Cu−1Ni−1Mg−2Mn piston alloys were investigated.The results show that the UV and UV...Effects of ultrasonic vibration(UV)and mechanical vibration(MV)on the Mn-rich phase modification and mechanical properties of Al−12Si−4Cu−1Ni−1Mg−2Mn piston alloys were investigated.The results show that the UV and UV+MV treatments can significantly refine and fragmentize the microstructures.In addition,UV treatment can significantly passivate the primary Mn-rich Al15Mn3Si2 intermetallics.The formation mechanisms of refinement and passivation of the grains and non-dendrite particles were discussed.Compared with the gravity die-cast alloys,the UV and UV+MV treated alloys exhibit improved tensile and creep resistance at room and elevated temperatures.These results can be attributed to the refinement of theα(Al)grains and the secondary intermetallics,the increased proportion of refined heat-resistant precipitates,and the formation of nano-sized Si particles.The ultimate tensile strength of the UV treated alloys at 350℃ exceeds that of commercial piston alloys.This indicates the high application potential of the developed piston alloys in density diesel engines.展开更多
Objective To observe the value of deep learning (DL) models for automatic classification of echocardiographic views. Methods Totally 100 patients after heart transplantation were retrospectively enrolled and divided i...Objective To observe the value of deep learning (DL) models for automatic classification of echocardiographic views. Methods Totally 100 patients after heart transplantation were retrospectively enrolled and divided into training set, validation set and test set at a ratio of 7 ∶ 2 ∶ 1. ResNet18, ResNet34, Swin Transformer and Swin Transformer V2 models were established based on 2D apical two chamber view, 2D apical three chamber view, 2D apical four chamber view, 2D subcostal view, parasternal long-axis view of left ventricle, short-axis view of great arteries, short-axis view of apex of left ventricle, short-axis view of papillary muscle of left ventricle, short-axis view of mitral valve of left ventricle, also 3D and CDFI views of echocardiography. The accuracy, precision, recall, F1 score and confusion matrix were used to evaluate the performance of each model for automatically classifying echocardiographic views. The interactive interface was designed based on Qt Designer software and deployed on the desktop. Results The performance of models for automatically classifying echocardiographic views in test set were all good, with relatively poor performance for 2D short-axis view of left ventricle and superior performance for 3D and CDFI views. Swin Transformer V2 was the optimal model for automatically classifying echocardiographic views, with high accuracy, precision, recall and F1 score was 92.56%, 89.01%, 89.97% and 89.31%, respectively, which also had the highest diagonal value in confusion matrix and showed the best classification effect on various views in t-SNE figure. Conclusion DL model had good performance for automatically classifying echocardiographic views, especially Swin Transformer V2 model had the best performance. Using interactive classification interface could improve the interpretability of prediction results to some extent.展开更多
Objective To observe the value of deep learning echocardiographic intelligent model for evaluation on left ventricular(LV)regional wall motion abnormalities(RWMA).Methods Apical two-chamber,three-chamber and four-cham...Objective To observe the value of deep learning echocardiographic intelligent model for evaluation on left ventricular(LV)regional wall motion abnormalities(RWMA).Methods Apical two-chamber,three-chamber and four-chamber views two-dimensional echocardiograms were obtained prospectively in 205 patients with coronary heart disease.The model for evaluating LV regional contractile function was constructed using a five-fold cross-validation method to automatically identify the presence of RWMA or not,and the performance of this model was assessed taken manual interpretation of RWMA as standards.Results Among 205 patients,RWMA was detected in totally 650 segments in 83 cases.LV myocardial segmentation model demonstrated good efficacy for delineation of LV myocardium.The average Dice similarity coefficient for LV myocardial segmentation results in the apical two-chamber,three-chamber and four-chamber views was 0.85,0.82 and 0.88,respectively.LV myocardial segmentation model accurately segmented LV myocardium in apical two-chamber,three-chamber and four-chamber views.The mean area under the curve(AUC)of RWMA identification model was 0.843±0.071,with sensitivity of(64.19±14.85)%,specificity of(89.44±7.31)%and accuracy of(85.22±4.37)%.Conclusion Deep learning echocardiographic intelligent model could be used to automatically evaluate LV regional contractile function,hence rapidly and accurately identifying RWMA.展开更多
文摘A comprehensive acoustical test was conducted in the traditional Ch ine se in-house theater, the theater of Shi`s residence in Tianjin. The measured pa rameters include reverberation time, clarity, lateral reflectance and IACC. Prim ary analysis was done with the test result.
基金Project(52202455)supported by the National Natural Science Foundation of ChinaProject(23A0017)supported by the Key Project of Scientific Research Project of Hunan Provincial Department of Education,China。
文摘In order to overcome the limitations of traditional microperforated plate with narrow sound absorption bandwidth and a single structure,two multi-cavity composite sound-absorbing materials were designed based on the shape of monoclinic crystals:uniaxial oblique structure(UOS)and biaxial oblique structure(BOS).Through finite element simulation and experimental research,the theoretical models of UOS and BOS were verified,and their sound absorption mechanisms were revealed.At the same time,the influence of multi-cavity composites on sound absorption performance was analyzed based on the theoretical model,and the influence of structural parameters on sound absorption performance was discussed.The research results show that,in the range of 100-2000 Hz,UOS has three sound absorption peaks and BOS has five sound absorption peaks.The frequency range of the half-absorption bandwidth(α>0.5)of UOS and BOS increases by 242% and 229%,respectively.Compared with traditional microperforated sound-absorbing structures,the series and parallel hybrid methods significantly increase the sound-absorbing bandwidth of the sound-absorbing structure.This research has guiding significance for noise control and has broad application prospects in the fields of transportation,construction,and mechanical design.
文摘Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).
基金Projects(52225403,U2013603,42377143)supported by the National Natural Science Foundation of ChinaProject(2023NSFSC0004)supported by the Sichuan Science and Technology Program,China+1 种基金Project(2023YFB2390200)supported by the National Key R&D Program-Young Scientist Program,ChinaProject(RCJC20210706091948015)supported by the Shenzhen Science Foundation for Distinguished Young Scholars,China。
文摘Laser technology holds significant promise for enhancing rock-breaking efficiency.Experimental investigations were carried out on sandstone subjected to laser radiation,aiming to elucidate its response mechanism to such radiation.The uniaxial compressive strength of sandstone notably decreases by 22.1%–54.7%following exposure to a 750 W laser for 30 s,indicating a substantial weakening effect.Furthermore,the elastic modulus and Poisson ratio of sandstone exhibit an average decrease of 33.7%and 25.9%,respectively.Simultaneously,laser radiation reduces the brittleness of sandstone,increases the dissipated energy proportion,and shifts the failure mode from tensile to tension-shear composite failure.Following laser radiation,both the number and energy of acoustic emission events in the sandstone register a substantial increase,with a more dispersed distribution of these events.In summary,laser radiation induces notable damage to the mechanical properties of sandstone,leading to a substantial decrease in elastic energy storage capacity.Laser rock breaking technology is expected to be applied in hard rock breaking engineering to significantly reduce the difficulty of rock breaking and improve rock breaking efficiency.
文摘Objective To investigate the value of polar residual network(PResNet)model for assisting evaluation on rat myocardial infarction(MI)segment in myocardial contrast echocardiography(MCE).Methods Twenty-five male SD rats were randomly divided into MI group(n=15)and sham operation group(n=10).MI models were established in MI group through ligation of the left anterior descending coronary artery using atraumatic suture,while no intervention was given to those in sham operation group after thoracotomy.MCE images of both basal and papillary muscle levels on the short axis section of left ventricles were acquired after 1 week,which were assessed independently by 2 junior and 2 senior ultrasound physicians.The evaluating efficacy of MI segment,the mean interpretation time and the consistency were compared whether under the assistance of PResNet model or not.Results No significant difference of efficacy of evaluation on MI segment was found for senior physicians with or without assistance of PResNet model(both P>0.05).Under the assistance of PResNet model,the efficacy of junior physicians for diagnosing MI segment was significantly improved compared with that without the assistance of PResNet model(both P<0.01),and was comparable to that of senior physicians.Under the assistance of PResNet model,the mean interpretation time of each physician was significantly shorter than that without assistance(all P<0.001),and the consistency between junior physicians and among junior and senior physicians were both moderate(Kappa=0.692,0.542),which became better under the assistance(Kappa=0.763,0.749).Conclusion PResNet could improve the efficacy of junior physicians for evaluation on rat MI segment in MCE images,shorten interpretation time with different aptitudes,also improve the consistency to some extent.
基金the National Natural Science Foundation of China(No.52265043)Science and Technology Plan,Guizhou Province,China(No.ZK2021(267))+2 种基金Technology Achievements Application and Industrialization Project,Guizhou Province,China(No.2021(067))Cultivation Project of Guizhou University,China(No.2019(23))Lastly,we thank the Shanghai Synchrotron Radiation Facility(SSRF)for providing the synchrotron radiation beamtime.
文摘Effects of ultrasonic vibration(UV)and mechanical vibration(MV)on the Mn-rich phase modification and mechanical properties of Al−12Si−4Cu−1Ni−1Mg−2Mn piston alloys were investigated.The results show that the UV and UV+MV treatments can significantly refine and fragmentize the microstructures.In addition,UV treatment can significantly passivate the primary Mn-rich Al15Mn3Si2 intermetallics.The formation mechanisms of refinement and passivation of the grains and non-dendrite particles were discussed.Compared with the gravity die-cast alloys,the UV and UV+MV treated alloys exhibit improved tensile and creep resistance at room and elevated temperatures.These results can be attributed to the refinement of theα(Al)grains and the secondary intermetallics,the increased proportion of refined heat-resistant precipitates,and the formation of nano-sized Si particles.The ultimate tensile strength of the UV treated alloys at 350℃ exceeds that of commercial piston alloys.This indicates the high application potential of the developed piston alloys in density diesel engines.
文摘Objective To observe the value of deep learning (DL) models for automatic classification of echocardiographic views. Methods Totally 100 patients after heart transplantation were retrospectively enrolled and divided into training set, validation set and test set at a ratio of 7 ∶ 2 ∶ 1. ResNet18, ResNet34, Swin Transformer and Swin Transformer V2 models were established based on 2D apical two chamber view, 2D apical three chamber view, 2D apical four chamber view, 2D subcostal view, parasternal long-axis view of left ventricle, short-axis view of great arteries, short-axis view of apex of left ventricle, short-axis view of papillary muscle of left ventricle, short-axis view of mitral valve of left ventricle, also 3D and CDFI views of echocardiography. The accuracy, precision, recall, F1 score and confusion matrix were used to evaluate the performance of each model for automatically classifying echocardiographic views. The interactive interface was designed based on Qt Designer software and deployed on the desktop. Results The performance of models for automatically classifying echocardiographic views in test set were all good, with relatively poor performance for 2D short-axis view of left ventricle and superior performance for 3D and CDFI views. Swin Transformer V2 was the optimal model for automatically classifying echocardiographic views, with high accuracy, precision, recall and F1 score was 92.56%, 89.01%, 89.97% and 89.31%, respectively, which also had the highest diagonal value in confusion matrix and showed the best classification effect on various views in t-SNE figure. Conclusion DL model had good performance for automatically classifying echocardiographic views, especially Swin Transformer V2 model had the best performance. Using interactive classification interface could improve the interpretability of prediction results to some extent.
文摘Objective To observe the value of deep learning echocardiographic intelligent model for evaluation on left ventricular(LV)regional wall motion abnormalities(RWMA).Methods Apical two-chamber,three-chamber and four-chamber views two-dimensional echocardiograms were obtained prospectively in 205 patients with coronary heart disease.The model for evaluating LV regional contractile function was constructed using a five-fold cross-validation method to automatically identify the presence of RWMA or not,and the performance of this model was assessed taken manual interpretation of RWMA as standards.Results Among 205 patients,RWMA was detected in totally 650 segments in 83 cases.LV myocardial segmentation model demonstrated good efficacy for delineation of LV myocardium.The average Dice similarity coefficient for LV myocardial segmentation results in the apical two-chamber,three-chamber and four-chamber views was 0.85,0.82 and 0.88,respectively.LV myocardial segmentation model accurately segmented LV myocardium in apical two-chamber,three-chamber and four-chamber views.The mean area under the curve(AUC)of RWMA identification model was 0.843±0.071,with sensitivity of(64.19±14.85)%,specificity of(89.44±7.31)%and accuracy of(85.22±4.37)%.Conclusion Deep learning echocardiographic intelligent model could be used to automatically evaluate LV regional contractile function,hence rapidly and accurately identifying RWMA.
