It has been revealed that the different morphologies of anodized TiO_2 nanotubes, especially nanotube diameters, triggered different cell behaviors. However, the influence of TiO_2 nanotubes with coexisting multi-size...It has been revealed that the different morphologies of anodized TiO_2 nanotubes, especially nanotube diameters, triggered different cell behaviors. However, the influence of TiO_2 nanotubes with coexisting multi-size diameters on cell behaviors is seldom reported. In this work, coexisting four-diameter TiO_2 nanotube samples, namely,one single substrate with the integration of four different nanotube diameters(60, 150, 250, and 350 nm), were prepared by repeated anodization. The boundaries between two different diameter regions show well-organized structure without obvious difference in height. The adhesion behaviors of MC3T3-E1 cells on the coexisting fourdiameter TiO_2 nanotube arrays were investigated. The results exhibit a significant difference of cell density between smaller diameters(60 and 150 nm) and larger diameters(250 and 350 nm) within 24 h incubation with the coexistence of different diameters, which is totally different from that on the single-diameter TiO_2 nanotube arrays. The coexistence of four different diameters does not change greatly the cell morphologies compared with the singlediameter nanotubes. The findings in this work are expected to offer further understanding of the interaction between cells and materials.展开更多
Reaction kinetics of nanoparticles can be controlled by tuning the Peclet number(Pe)as it is an essential parameter in synthesis of multi-sized nanoparticles.Herein,we propose to implement a self-driven multi-dimensio...Reaction kinetics of nanoparticles can be controlled by tuning the Peclet number(Pe)as it is an essential parameter in synthesis of multi-sized nanoparticles.Herein,we propose to implement a self-driven multi-dimension microchannels reactor(MMR)for the one droplet synthesis of multi-sized nanoparticles.By carefully controlling the Pe at the gas-liquid interface,the newly formed seed crystals selectively accumulate and grow to a specific size.By the combination of microchannels of different widths and lengths,one droplet reaction in the same apparatus achieves the synchronous synthesis of diverse nanoparticles.MMR enables precise control of nanoparticle diameter at 5 nm precision in the range of 10-110 nm.The use of MMR can be extended to the synthesis of uniform Ag,Au,Pt,and Pd nanoparticles,opening towards the production and engineering of nanostructured materials.This approach gives the chance to regulate the accumulation probability for precise synthesis of nanoparticles with different diameters.展开更多
The 3D turbulence k-ε model flow of the steel melt （continuous phase） and the trajectories of individual gas bubbles （dispersed phase） in a continuous casting mold were simulated using an Eulerian-Lagrangian appr...The 3D turbulence k-ε model flow of the steel melt （continuous phase） and the trajectories of individual gas bubbles （dispersed phase） in a continuous casting mold were simulated using an Eulerian-Lagrangian approach. In order to investigate the effect of bubble size distribution, the radii of bubbles are set with an initial value of 0. 1- 2.5 mm which follows the normal distribution. The presented results indicate that, in the submerged entry nozzle （SEN）, the distribution of void fraction is only near the wall. Due to the fact that the bubbles motion is only limited to the wall, the deoxidization products have no access to contacting the wall, which prevents clogging. In the mold, the bubbles with a radius of 0. 25--2.5 mm will move to the top surface. Larger bubbles issuing out of the ports will attack the menis- cus and induce the fluid flows upwards in the top surface near the nozzle. It may induce mold powder entrapment into the mold. The bubbles with a radius of 0.1--0.25 mm will move to the zone near the narrow surface and the wide surface. These small bubbles will probably be trapped by the solidification front. Most of the bubbles moving to the narrow surface will flow with the ascending flow, while others will flow with the descending flow.展开更多
With the growth of the Internet,more and more business is being done online,for example,online offices,online education and so on.While this makes people’s lives more convenient,it also increases the risk of the netw...With the growth of the Internet,more and more business is being done online,for example,online offices,online education and so on.While this makes people’s lives more convenient,it also increases the risk of the network being attacked by malicious code.Therefore,it is important to identify malicious codes on computer systems efficiently.However,most of the existing malicious code detection methods have two problems:(1)The ability of the model to extract features is weak,resulting in poor model performance.(2)The large scale of model data leads to difficulties deploying on devices with limited resources.Therefore,this paper proposes a lightweight malicious code identification model Lightweight Malicious Code Classification Method Based on Improved SqueezeNet(LCMISNet).In this paper,the MFire lightweight feature extraction module is constructed by proposing a feature slicing module and a multi-size depthwise separable convolution module.The feature slicing module reduces the number of parameters by grouping features.The multi-size depthwise separable convolution module reduces the number of parameters and enhances the feature extraction capability by replacing the standard convolution with depthwise separable convolution with different convolution kernel sizes.In addition,this paper also proposes a feature splicing module to connect the MFire lightweight feature extraction module based on the feature reuse and constructs the lightweight model LCMISNet.The malicious code recognition accuracy of LCMISNet on the BIG 2015 dataset and the Malimg dataset reaches 98.90% and 99.58%,respectively.It proves that LCMISNet has a powerful malicious code recognition performance.In addition,compared with other network models,LCMISNet has better performance,and a lower number of parameters and computations.展开更多
基金supported by the National Natural Science Foundation of China(No.51401126,No.51271117)Shanghai Committee of Science and Technology,China(No.14441901800)
文摘It has been revealed that the different morphologies of anodized TiO_2 nanotubes, especially nanotube diameters, triggered different cell behaviors. However, the influence of TiO_2 nanotubes with coexisting multi-size diameters on cell behaviors is seldom reported. In this work, coexisting four-diameter TiO_2 nanotube samples, namely,one single substrate with the integration of four different nanotube diameters(60, 150, 250, and 350 nm), were prepared by repeated anodization. The boundaries between two different diameter regions show well-organized structure without obvious difference in height. The adhesion behaviors of MC3T3-E1 cells on the coexisting fourdiameter TiO_2 nanotube arrays were investigated. The results exhibit a significant difference of cell density between smaller diameters(60 and 150 nm) and larger diameters(250 and 350 nm) within 24 h incubation with the coexistence of different diameters, which is totally different from that on the single-diameter TiO_2 nanotube arrays. The coexistence of four different diameters does not change greatly the cell morphologies compared with the singlediameter nanotubes. The findings in this work are expected to offer further understanding of the interaction between cells and materials.
基金supported by the Beijing Nova Program from Beijing Municipal Science&Technology Commission(Nos.Z201100006820037 and Z211100002121001)the National Key R&D Program of China(No.2018YFA0208501)+3 种基金the National Natural Science Foundation of China(Nos.22075296,91963212,and 51961145102)the Youth Innovation Promotion Association,the Chinese Academy of Sciences(No.2020032)Beijing National Laboratory for Molecular Sciences(No.BNLMS-CXXM-202005)F.F.Q.and J.C.acknowledge the Swiss National Super Computing Center(Project No.s1081)for providing the computing support.B.D.C.acknowledges Jiarong Yang for his support in graphing.
文摘Reaction kinetics of nanoparticles can be controlled by tuning the Peclet number(Pe)as it is an essential parameter in synthesis of multi-sized nanoparticles.Herein,we propose to implement a self-driven multi-dimension microchannels reactor(MMR)for the one droplet synthesis of multi-sized nanoparticles.By carefully controlling the Pe at the gas-liquid interface,the newly formed seed crystals selectively accumulate and grow to a specific size.By the combination of microchannels of different widths and lengths,one droplet reaction in the same apparatus achieves the synchronous synthesis of diverse nanoparticles.MMR enables precise control of nanoparticle diameter at 5 nm precision in the range of 10-110 nm.The use of MMR can be extended to the synthesis of uniform Ag,Au,Pt,and Pd nanoparticles,opening towards the production and engineering of nanostructured materials.This approach gives the chance to regulate the accumulation probability for precise synthesis of nanoparticles with different diameters.
基金Item Sponsored by National Natural Science Foundation of China(50874130,50974034)
文摘The 3D turbulence k-ε model flow of the steel melt （continuous phase） and the trajectories of individual gas bubbles （dispersed phase） in a continuous casting mold were simulated using an Eulerian-Lagrangian approach. In order to investigate the effect of bubble size distribution, the radii of bubbles are set with an initial value of 0. 1- 2.5 mm which follows the normal distribution. The presented results indicate that, in the submerged entry nozzle （SEN）, the distribution of void fraction is only near the wall. Due to the fact that the bubbles motion is only limited to the wall, the deoxidization products have no access to contacting the wall, which prevents clogging. In the mold, the bubbles with a radius of 0. 25--2.5 mm will move to the top surface. Larger bubbles issuing out of the ports will attack the menis- cus and induce the fluid flows upwards in the top surface near the nozzle. It may induce mold powder entrapment into the mold. The bubbles with a radius of 0.1--0.25 mm will move to the zone near the narrow surface and the wide surface. These small bubbles will probably be trapped by the solidification front. Most of the bubbles moving to the narrow surface will flow with the ascending flow, while others will flow with the descending flow.
文摘With the growth of the Internet,more and more business is being done online,for example,online offices,online education and so on.While this makes people’s lives more convenient,it also increases the risk of the network being attacked by malicious code.Therefore,it is important to identify malicious codes on computer systems efficiently.However,most of the existing malicious code detection methods have two problems:(1)The ability of the model to extract features is weak,resulting in poor model performance.(2)The large scale of model data leads to difficulties deploying on devices with limited resources.Therefore,this paper proposes a lightweight malicious code identification model Lightweight Malicious Code Classification Method Based on Improved SqueezeNet(LCMISNet).In this paper,the MFire lightweight feature extraction module is constructed by proposing a feature slicing module and a multi-size depthwise separable convolution module.The feature slicing module reduces the number of parameters by grouping features.The multi-size depthwise separable convolution module reduces the number of parameters and enhances the feature extraction capability by replacing the standard convolution with depthwise separable convolution with different convolution kernel sizes.In addition,this paper also proposes a feature splicing module to connect the MFire lightweight feature extraction module based on the feature reuse and constructs the lightweight model LCMISNet.The malicious code recognition accuracy of LCMISNet on the BIG 2015 dataset and the Malimg dataset reaches 98.90% and 99.58%,respectively.It proves that LCMISNet has a powerful malicious code recognition performance.In addition,compared with other network models,LCMISNet has better performance,and a lower number of parameters and computations.
