A nonlinear mathematical model of the injection molding process for electrohydraulic servo injection molding machine (IMM) is developed.It was found necessary to consider the characteristics of asymmetric cylinder for...A nonlinear mathematical model of the injection molding process for electrohydraulic servo injection molding machine (IMM) is developed.It was found necessary to consider the characteristics of asymmetric cylinder for electrohydraulic servo IMM.The model is based on the dynamics of the machine including servo valve,asymmetric cylinder and screw,and the non-Newtonian flow behavior of polymer melt in injection molding is also considered.The performance of the model was evaluated based on novel approach of molding - injection and compress molding,and the results of simulation and experimental data demonstrate the effectiveness of the model.展开更多
Icing on the surface of aircraft will not only aggravate its quality and affect flight control,but even cause safety accidents,which is one of the important factors restricting all-weather flight.Bio-inspired anti-ici...Icing on the surface of aircraft will not only aggravate its quality and affect flight control,but even cause safety accidents,which is one of the important factors restricting all-weather flight.Bio-inspired anti-icing surfaces have gained great attention recently due to their low-hysteresis,non-stick properties,slow nucleation rate and low ice adhesion strength.These bio-inspired anti-icing surfaces,such as superhydrophobic surfaces,slippery liquid-infused porous surfaces and quasi-liquid film surfaces,have realized excellent anti-icing performance at various stages of icing.However,for harsh environment,there are still many problems and challenges.From the perspective of bioinspiration,the mechanism of icing nucleation,liquid bounce and ice adhesion has been reviewed together with the application progress and bottleneck issues about anti-icing in view of the process of icing.Subsequently,the reliability and development prospect of active,passive and active-passive integrated anti-icing technology are discussed,respectively.展开更多
A method of B-spline transform for signal feature extraction is developed. With the B-spline, the log-signal space is mapped into the vector space. An efficient algorithm based on Support Vector Machine (SVM ) to auto...A method of B-spline transform for signal feature extraction is developed. With the B-spline, the log-signal space is mapped into the vector space. An efficient algorithm based on Support Vector Machine (SVM ) to automatically identify the water-flooded status of oil-saturated stratum is described. The experiments show that this algorithm can improve the performances for the identification and the generalization in the case of a limited set of samples.展开更多
Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Objective：To explore the effects of Xingnaojing injection on cerebral edema and blood-brain barrier （BBB） in rats following traumatic brain injury （TBI）.Methods： A total of 108 adult male Sprague-Dawley rats wer...Objective：To explore the effects of Xingnaojing injection on cerebral edema and blood-brain barrier （BBB） in rats following traumatic brain injury （TBI）.Methods： A total of 108 adult male Sprague-Dawley rats were used as subjects and randomly assigned to three groups：sham-operation,TBI and Xingnaojing injection was set up by the improved device of Feeney＇s weightcontent and BBB permeability expressed as Evans blue content were measured at 1, 3, 5 and 7 days after surgery.Results： In sham-operation group, brain water content and Evans blue content in brain tissue were 78.97%±1.22%and 5.13μg±0.71μg. Following TBI, water content in brain tissue was increased significantly at 1, 3, 5 and 7 days （83.49%±0.54%, 82.74%±0.72%, 80.22%±0.68%, 79.21%±0.60%）, being significantly higher than that in sham operation group （P〈0.05）. Evans blue content was increased in TBI group （16.54 μg±0.60 μg, 14.92μg±0.71μg, 12.44 μg ±0.92μg, 10.14μg±0.52 μg） as compared with sham-operation group（P〈0.05）. After treatment with Xingnaojing injection, brain water content decreased as compared with TBI group （81.91%±1.04%, 80.38%±0.72%, 79.54%±0.58%,78.60%±0.77%, P〈0.05）. Xingnaojing injection also reduced the leakage of BBB as compared with TBI group （15.11 μg± 0.63 μg, 13.62 μg±0.85μg, 10.06 μg±0.67 μg, 9.54 μg±0.41 μg,P〈0.05）.Conclusion： Xingnaojing injection could alleviate cerebral edema following TBI via reducing permeability ofBBB.展开更多
基金Foundation item: The National Torch Program of China (No. 2001EB000991)
文摘A nonlinear mathematical model of the injection molding process for electrohydraulic servo injection molding machine (IMM) is developed.It was found necessary to consider the characteristics of asymmetric cylinder for electrohydraulic servo IMM.The model is based on the dynamics of the machine including servo valve,asymmetric cylinder and screw,and the non-Newtonian flow behavior of polymer melt in injection molding is also considered.The performance of the model was evaluated based on novel approach of molding - injection and compress molding,and the results of simulation and experimental data demonstrate the effectiveness of the model.
基金financially supported by the National Natural Science Foundation of China(Nos.T2121003,51725501,51935001,52205297).
文摘Icing on the surface of aircraft will not only aggravate its quality and affect flight control,but even cause safety accidents,which is one of the important factors restricting all-weather flight.Bio-inspired anti-icing surfaces have gained great attention recently due to their low-hysteresis,non-stick properties,slow nucleation rate and low ice adhesion strength.These bio-inspired anti-icing surfaces,such as superhydrophobic surfaces,slippery liquid-infused porous surfaces and quasi-liquid film surfaces,have realized excellent anti-icing performance at various stages of icing.However,for harsh environment,there are still many problems and challenges.From the perspective of bioinspiration,the mechanism of icing nucleation,liquid bounce and ice adhesion has been reviewed together with the application progress and bottleneck issues about anti-icing in view of the process of icing.Subsequently,the reliability and development prospect of active,passive and active-passive integrated anti-icing technology are discussed,respectively.
基金Supported by the Natural Science Foundation of Heilong- jiang Province (No.F01-20).
文摘A method of B-spline transform for signal feature extraction is developed. With the B-spline, the log-signal space is mapped into the vector space. An efficient algorithm based on Support Vector Machine (SVM ) to automatically identify the water-flooded status of oil-saturated stratum is described. The experiments show that this algorithm can improve the performances for the identification and the generalization in the case of a limited set of samples.
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
文摘Objective：To explore the effects of Xingnaojing injection on cerebral edema and blood-brain barrier （BBB） in rats following traumatic brain injury （TBI）.Methods： A total of 108 adult male Sprague-Dawley rats were used as subjects and randomly assigned to three groups：sham-operation,TBI and Xingnaojing injection was set up by the improved device of Feeney＇s weightcontent and BBB permeability expressed as Evans blue content were measured at 1, 3, 5 and 7 days after surgery.Results： In sham-operation group, brain water content and Evans blue content in brain tissue were 78.97%±1.22%and 5.13μg±0.71μg. Following TBI, water content in brain tissue was increased significantly at 1, 3, 5 and 7 days （83.49%±0.54%, 82.74%±0.72%, 80.22%±0.68%, 79.21%±0.60%）, being significantly higher than that in sham operation group （P〈0.05）. Evans blue content was increased in TBI group （16.54 μg±0.60 μg, 14.92μg±0.71μg, 12.44 μg ±0.92μg, 10.14μg±0.52 μg） as compared with sham-operation group（P〈0.05）. After treatment with Xingnaojing injection, brain water content decreased as compared with TBI group （81.91%±1.04%, 80.38%±0.72%, 79.54%±0.58%,78.60%±0.77%, P〈0.05）. Xingnaojing injection also reduced the leakage of BBB as compared with TBI group （15.11 μg± 0.63 μg, 13.62 μg±0.85μg, 10.06 μg±0.67 μg, 9.54 μg±0.41 μg,P〈0.05）.Conclusion： Xingnaojing injection could alleviate cerebral edema following TBI via reducing permeability ofBBB.
