The deformation behaviors of a new quaternary Mg-6Zn-1.5Cu-0.5Zr alloy at temperatures of 523-673 K and strain rates of 0.001-1 s-1 were studied by compressive tests using a Gleeble 3800 thermal-simulator.The results ...The deformation behaviors of a new quaternary Mg-6Zn-1.5Cu-0.5Zr alloy at temperatures of 523-673 K and strain rates of 0.001-1 s-1 were studied by compressive tests using a Gleeble 3800 thermal-simulator.The results show that the flow stress increases as the deformation temperature decreases or as the strain rate increases.A strain-dependent constitutive equation and a feed-forward back-propagation artificial neural network were used to predict flow stress,which showed good agreement with experimental data.The processing map suggests that the domains of 643-673 K and 0.001-0.01 s-1 are corresponded to optimum conditions for hot working of the T4-treated Mg-6Zn-1.5Cu-0.5Zr alloy.展开更多
Based on the experimental data of Ti40 alloy obtained from Gleeble-1500 thermal simulator,an artificial neural network model of high temperature flow stress as a function of strain,strain rate and temperature was esta...Based on the experimental data of Ti40 alloy obtained from Gleeble-1500 thermal simulator,an artificial neural network model of high temperature flow stress as a function of strain,strain rate and temperature was established.In the network model,the input parameters of the model are strain,logarithm strain rate and temperature while flow stress is the output parameter.Multilayer perceptron（MLP） architecture with back-propagation algorithm is utilized.The present study achieves a good performance of the artificial neural network（ANN） model,and the predicted results are in agreement with experimental values.A processing map of Ti40 alloy is obtained with the flow stress predicted by the trained neural network model.The processing map developed by ANN model can efficiently track dynamic recrystallization and flow localization regions of Ti40 alloy during deforming.Subsequently,the safe and instable domains of hot working of Ti40 alloy are identified and validated through microstructural investigations.展开更多
Back-propagation artificial neural network (BPANN) is used in ball backward spinning in order to form thin-walled tubular parts with longitudinal inner ribs. By selecting the process parameters which have a great infl...Back-propagation artificial neural network (BPANN) is used in ball backward spinning in order to form thin-walled tubular parts with longitudinal inner ribs. By selecting the process parameters which have a great influence on the height of inner ribs as well as fish scale on the surface of the spun part, a BPANN of 3-8-1 structure is established for predicting the height of inner rib and recognizing the fish scale defect. Experiments data have proved that the average relative error between the measured value and the predicted value of the height of inner rib is not more than 5%. It is evident that BPANN can not only predict the height of inner ribs of the spun part accurately, but recognize and prevent the occurrence of the quality defect of fish scale successfully, and combining BPANN with the ball backward spinning is essential to obtain the desired spun part.展开更多
In order to catch more process details in chemical processes, adynamic model for prediction of process trends is proposed bymodifying traditional time-series ANN (artificial neural networks)model with impulse response...In order to catch more process details in chemical processes, adynamic model for prediction of process trends is proposed bymodifying traditional time-series ANN (artificial neural networks)model with impulse response identification means. The applicationresults of the model is briefly discussed.展开更多
Soil macronutrients(i.e. nitrogen(N), phosphorus(P), and potassium(K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of thi...Soil macronutrients(i.e. nitrogen(N), phosphorus(P), and potassium(K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks(ANN) and two geostatistical methods(geographically weighted regression(GWR) and cokriging(CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil(0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration(n = 84) and validation(n = 22). Chemical and physical variables including clay, p H and organic carbon(OC) were used as auxiliary soil variables to estimate the N, P and K contents. Results showed that the ANN model(with coefficient of determination R^2 = 0.922 and root mean square error RMSE = 0.0079%) was more accurate compared to the CK model(with R^2 = 0.612 and RMSE = 0.0094%), and the GWR model(with R^2 = 0.872 and RMSE = 0.0089%) to estimate the N variable. The ANN model estimated the P with the RMSE of 3.630 ppm, which was respectively 28.93% and 20.00% less than the RMSE of 4.680 ppm and 4.357 ppm from the CK and GWR models. The estimated K by CK, GWR and ANN models have the RMSE of 76.794 ppm, 75.790 ppm and 52.484 ppm. Results indicated that the performance of the CK model for estimation of macro nutrients(N, P and K) was slightly lower than the GWR model. Also, the accuracy of the ANN model was higher than CK and GWR models, which proved to be more effective and reliable methods for estimating macro nutrients.展开更多
Retinal degenerative diseases may induce the degeneration of outer retina and in turn,blindness.Nevertheless,due to the maintenance of inner retina,the coding and processing of visual neurons responses are still able ...Retinal degenerative diseases may induce the degeneration of outer retina and in turn,blindness.Nevertheless,due to the maintenance of inner retina,the coding and processing of visual neurons responses are still able to be executed naturally.Therefore,an effective retinal prosthesis device may be developed by mimicking the function of outer retina:transferring the visual light into artificial stimulus and delivering the stimulus to the retina aiming to evoke the neural responses.As two main developing directions for current retinal prosthesis,epiretinal(ER)and subretinal(SR)prosthesis are both undergoing experimental stage and possessing advantages and limitations.Further investigations in power supply,biocompatibility,etc.are still required.Additionally,suprachoroidal transretinal stimulation(STS)and neurotransmitter-induced stimulation as some other alternatives in retinal prosthesis are also considered as promising research directions,although they are not mature enough to be applied commercially,either.展开更多
This article presents an Artificial Neural Network （ANN） architecture to model the Electrical Discharge Machining （EDM） process. It is aimed to develop the ANN model using an input-output pattern of raw data colle...This article presents an Artificial Neural Network （ANN） architecture to model the Electrical Discharge Machining （EDM） process. It is aimed to develop the ANN model using an input-output pattern of raw data collected from an experimental of EDM process, whereas several research objectives have been outlined such as experimenting machining material for selected gap current, identifying machining parameters for ANN variables and selecting appropriate size of data selection. The experimental data （input variables） of copper-electrode and steel-workpiece is based on a selected gap current where pulse on time, pulse off time and sparking frequency have been chosen at optimum value of Material Removal Rate （MRR）. In this paper, the result has significantly demonstrated that the ANN model is capable of predicting the MRR with low percentage prediction error when compared with the experimental result.展开更多
Based on the Residual Oil Hydrodesulfurization Treatment Unit (S-RHT), the n-order reaction kinetic model for residual oil HDS reactions and artificial neural network (ANN) model were developed to determine the sulfur...Based on the Residual Oil Hydrodesulfurization Treatment Unit (S-RHT), the n-order reaction kinetic model for residual oil HDS reactions and artificial neural network (ANN) model were developed to determine the sulfur content of hydrogenated residual oil. The established ANN model covered 4 input variables, 1 output variable and 1 hidden layer with 15 neurons. The comparison between the results of two models was listed. The results showed that the predicted mean relative errors of the two models with three different sample data were less than 5% and both the two models had good predictive precision and extrapolative feature for the HDS process. The mean relative error of 5 sets of testing data of the ANN model was 1.62%—3.23%, all of which were smaller than that of the common mechanism model (3.47%— 4.13%). It showed that the ANN model was better than the mechanism model both in terms of fitting results and fitting difficulty. The models could be easily applied in practice and could also provide a reference for the further research of residual oil HDS process.展开更多
Objective To observe the change of the neuropeptide pro-protein processing system in the ischemic retina ganglion cell-5(RGC-5) cells,pro-protein convertase-2(PC2),carboxypeptidase-E(CPE) and preproneuropeptide Y(prep...Objective To observe the change of the neuropeptide pro-protein processing system in the ischemic retina ganglion cell-5(RGC-5) cells,pro-protein convertase-2(PC2),carboxypeptidase-E(CPE) and preproneuropeptide Y(preproNPY) protein levels in the ischemic RGC-5 cells and conditioned medium were analyzed. Methods The RGC-5 cell was differentiated in 0.1 μmol/L staurosporine for 24 h and then stressed by different doses of oxygen and glucose deprivation(OGD). The acute or chronic OGD-induced cell death rates w...展开更多
Emerging studies support that RNA-binding proteins （RBPs） play critical roles in human biology and pathogenesis. RBPs are essential players in RNA processing and metabolism, including pre-mRNA splicing, polyadenylat...Emerging studies support that RNA-binding proteins （RBPs） play critical roles in human biology and pathogenesis. RBPs are essential players in RNA processing and metabolism, including pre-mRNA splicing, polyadenylation, transport, surveillance, mRNA localization, mRNA stability control, translational control and editing of various types of RNAs. Aberrant expression of and mutations in RBP genes affect various steps of RNA processing, altering target gene function. RBPs have been associ- ated with various diseases, including neurological diseases. Here, we mainly focus on selected RNA-binding proteins including Nova-i/Nova-2, HuR/HuB/HuC/HuD, TDP-43, Fus, Rbfoxl/Rbfox2, QKI and FMRP, discussing their function and roles in human diseases.展开更多
基金supported by the R&D Program of Korea Institute of Materials Sciencethe World Premier Materials Program funded by The Ministry of Knowledge Economy,Koreasupport from China Scholarship Council(CSC)
文摘The deformation behaviors of a new quaternary Mg-6Zn-1.5Cu-0.5Zr alloy at temperatures of 523-673 K and strain rates of 0.001-1 s-1 were studied by compressive tests using a Gleeble 3800 thermal-simulator.The results show that the flow stress increases as the deformation temperature decreases or as the strain rate increases.A strain-dependent constitutive equation and a feed-forward back-propagation artificial neural network were used to predict flow stress,which showed good agreement with experimental data.The processing map suggests that the domains of 643-673 K and 0.001-0.01 s-1 are corresponded to optimum conditions for hot working of the T4-treated Mg-6Zn-1.5Cu-0.5Zr alloy.
基金Project(2007CB613807)supported by the National Basic Research Program of ChinaProject(NCET-07-0696)supported by the New Century Excellent Talents in University,ChinaProject(35-TP-2009)supported by the Fund of the State Key Laboratory of Solidification Processing in Northwestern Polytechnical University,China
文摘Based on the experimental data of Ti40 alloy obtained from Gleeble-1500 thermal simulator,an artificial neural network model of high temperature flow stress as a function of strain,strain rate and temperature was established.In the network model,the input parameters of the model are strain,logarithm strain rate and temperature while flow stress is the output parameter.Multilayer perceptron（MLP） architecture with back-propagation algorithm is utilized.The present study achieves a good performance of the artificial neural network（ANN） model,and the predicted results are in agreement with experimental values.A processing map of Ti40 alloy is obtained with the flow stress predicted by the trained neural network model.The processing map developed by ANN model can efficiently track dynamic recrystallization and flow localization regions of Ti40 alloy during deforming.Subsequently,the safe and instable domains of hot working of Ti40 alloy are identified and validated through microstructural investigations.
文摘Back-propagation artificial neural network (BPANN) is used in ball backward spinning in order to form thin-walled tubular parts with longitudinal inner ribs. By selecting the process parameters which have a great influence on the height of inner ribs as well as fish scale on the surface of the spun part, a BPANN of 3-8-1 structure is established for predicting the height of inner rib and recognizing the fish scale defect. Experiments data have proved that the average relative error between the measured value and the predicted value of the height of inner rib is not more than 5%. It is evident that BPANN can not only predict the height of inner ribs of the spun part accurately, but recognize and prevent the occurrence of the quality defect of fish scale successfully, and combining BPANN with the ball backward spinning is essential to obtain the desired spun part.
文摘In order to catch more process details in chemical processes, adynamic model for prediction of process trends is proposed bymodifying traditional time-series ANN (artificial neural networks)model with impulse response identification means. The applicationresults of the model is briefly discussed.
基金Foundation item:Under the auspices of Shahrood University of Technology,Iran(No.348517)
文摘Soil macronutrients(i.e. nitrogen(N), phosphorus(P), and potassium(K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks(ANN) and two geostatistical methods(geographically weighted regression(GWR) and cokriging(CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil(0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration(n = 84) and validation(n = 22). Chemical and physical variables including clay, p H and organic carbon(OC) were used as auxiliary soil variables to estimate the N, P and K contents. Results showed that the ANN model(with coefficient of determination R^2 = 0.922 and root mean square error RMSE = 0.0079%) was more accurate compared to the CK model(with R^2 = 0.612 and RMSE = 0.0094%), and the GWR model(with R^2 = 0.872 and RMSE = 0.0089%) to estimate the N variable. The ANN model estimated the P with the RMSE of 3.630 ppm, which was respectively 28.93% and 20.00% less than the RMSE of 4.680 ppm and 4.357 ppm from the CK and GWR models. The estimated K by CK, GWR and ANN models have the RMSE of 76.794 ppm, 75.790 ppm and 52.484 ppm. Results indicated that the performance of the CK model for estimation of macro nutrients(N, P and K) was slightly lower than the GWR model. Also, the accuracy of the ANN model was higher than CK and GWR models, which proved to be more effective and reliable methods for estimating macro nutrients.
文摘Retinal degenerative diseases may induce the degeneration of outer retina and in turn,blindness.Nevertheless,due to the maintenance of inner retina,the coding and processing of visual neurons responses are still able to be executed naturally.Therefore,an effective retinal prosthesis device may be developed by mimicking the function of outer retina:transferring the visual light into artificial stimulus and delivering the stimulus to the retina aiming to evoke the neural responses.As two main developing directions for current retinal prosthesis,epiretinal(ER)and subretinal(SR)prosthesis are both undergoing experimental stage and possessing advantages and limitations.Further investigations in power supply,biocompatibility,etc.are still required.Additionally,suprachoroidal transretinal stimulation(STS)and neurotransmitter-induced stimulation as some other alternatives in retinal prosthesis are also considered as promising research directions,although they are not mature enough to be applied commercially,either.
文摘This article presents an Artificial Neural Network （ANN） architecture to model the Electrical Discharge Machining （EDM） process. It is aimed to develop the ANN model using an input-output pattern of raw data collected from an experimental of EDM process, whereas several research objectives have been outlined such as experimenting machining material for selected gap current, identifying machining parameters for ANN variables and selecting appropriate size of data selection. The experimental data （input variables） of copper-electrode and steel-workpiece is based on a selected gap current where pulse on time, pulse off time and sparking frequency have been chosen at optimum value of Material Removal Rate （MRR）. In this paper, the result has significantly demonstrated that the ANN model is capable of predicting the MRR with low percentage prediction error when compared with the experimental result.
文摘Based on the Residual Oil Hydrodesulfurization Treatment Unit (S-RHT), the n-order reaction kinetic model for residual oil HDS reactions and artificial neural network (ANN) model were developed to determine the sulfur content of hydrogenated residual oil. The established ANN model covered 4 input variables, 1 output variable and 1 hidden layer with 15 neurons. The comparison between the results of two models was listed. The results showed that the predicted mean relative errors of the two models with three different sample data were less than 5% and both the two models had good predictive precision and extrapolative feature for the HDS process. The mean relative error of 5 sets of testing data of the ANN model was 1.62%—3.23%, all of which were smaller than that of the common mechanism model (3.47%— 4.13%). It showed that the ANN model was better than the mechanism model both in terms of fitting results and fitting difficulty. The models could be easily applied in practice and could also provide a reference for the further research of residual oil HDS process.
基金supported by Guangdong Pharmaceutical University Grant (No. 2005SMK22) and Key-Teacher Training Grant.
文摘Objective To observe the change of the neuropeptide pro-protein processing system in the ischemic retina ganglion cell-5(RGC-5) cells,pro-protein convertase-2(PC2),carboxypeptidase-E(CPE) and preproneuropeptide Y(preproNPY) protein levels in the ischemic RGC-5 cells and conditioned medium were analyzed. Methods The RGC-5 cell was differentiated in 0.1 μmol/L staurosporine for 24 h and then stressed by different doses of oxygen and glucose deprivation(OGD). The acute or chronic OGD-induced cell death rates w...
基金Zhou HuaLin is supported by National Basic Research Program of China(2013CB917803)research fund for the State Key Laboratory of Cog-nitive Neuroscience and Learning from Institute of Biophysics,Chinese Academy of Sciences(7Y1SNY7007)+3 种基金supported by the Ross Maclean Senior Research Fellowship and the Peter Goodenough BequestZhu Li and Liu JiangHong are supported by grants from the Na-tional Major Basic Research Program of China(2010CB529603)the National Natural Science Foundation of China(91132710,31200561)Jane Y.Wu is supported by the US National Institutes of Health
文摘Emerging studies support that RNA-binding proteins （RBPs） play critical roles in human biology and pathogenesis. RBPs are essential players in RNA processing and metabolism, including pre-mRNA splicing, polyadenylation, transport, surveillance, mRNA localization, mRNA stability control, translational control and editing of various types of RNAs. Aberrant expression of and mutations in RBP genes affect various steps of RNA processing, altering target gene function. RBPs have been associ- ated with various diseases, including neurological diseases. Here, we mainly focus on selected RNA-binding proteins including Nova-i/Nova-2, HuR/HuB/HuC/HuD, TDP-43, Fus, Rbfoxl/Rbfox2, QKI and FMRP, discussing their function and roles in human diseases.
