The data in Mobile Edge Computing(MEC)contains tremendousmarket value,and data sharing canmaximize the usefulness of the data.However,certain data is quite sensitive,and sharing it directly may violate privacy.Vertica...The data in Mobile Edge Computing(MEC)contains tremendousmarket value,and data sharing canmaximize the usefulness of the data.However,certain data is quite sensitive,and sharing it directly may violate privacy.Vertical Federated Learning(VFL)is a secure distributed machine learning framework that completes joint model training by passing encryptedmodel parameters rather than raw data,so there is no data privacy leakage during the training process.Therefore,the VFL can build a bridge between data demander and owner to realize data sharing while protecting data privacy.Typically,the VFL requires a third party for key distribution and decryption of training results.In this article,we employ the consortium blockchain instead of the traditional third party and design a VFL architecture based on the consortium blockchain for data sharing in MEC.More specifically,we propose a V-Raft consensus algorithm based on Verifiable Random Functions(VRFs),which is a variant of the Raft.The VRaft is able to elect leader quickly and stably to assist data demander and owner to complete data sharing by VFL.Moreover,we apply secret sharing todistribute the private key to avoid the situationwhere the training result cannot be decrypted if the leader crashes.Finally,we analyzed the performance of the V-Raft and carried out simulation experiments,and the results show that compared with Raft,the V-Raft has higher efficiency and better scalability.展开更多
Using the lattice Boltzmann multiphase model,numerical simulations have been performed to understand the dynamics of droplet formation in a microfluidic cross-junction.The influence of capillary number,flow rate ratio...Using the lattice Boltzmann multiphase model,numerical simulations have been performed to understand the dynamics of droplet formation in a microfluidic cross-junction.The influence of capillary number,flow rate ratio,viscosity ratio,and viscosity of the continuous phase on droplet formation has been systematically studied over a wide range of capillary numbers.Two different regimes,namely the squeezinglike regime and the dripping regime,are clearly identified with the transition occurring at a critical capillary number Cacr.Generally,large flow rate ratio is expected to produce big droplets,while increasing capillary number will reduce droplet size.In the squeezing-like regime(Ca≤Cacr),droplet breakup process is dominated by the squeezing pressure and the viscous force;while in the dripping regime(Ca>Cacr),the viscous force is dominant and the droplet size becomes independent of the flow rate ratio as the capillary number increases.In addition,the droplet size weakly depends on the viscosity ratio in both regimes and decreases when the viscosity of the continuous phase increases.Finally,a scaling law is established to predict the droplet size.展开更多
A novel and efficient approach to sulfonamides has been developed. Using TBHP as the oxidant and NH4I （20 mol%） as the catalyst, arylsulfonyl hydrazides reacted with amines to provide sulfonamides in moderate to goo...A novel and efficient approach to sulfonamides has been developed. Using TBHP as the oxidant and NH4I （20 mol%） as the catalyst, arylsulfonyl hydrazides reacted with amines to provide sulfonamides in moderate to good yields. Possible reaction pathway for the formation of the products was also discussed in this paper.展开更多
A new protocol for the synthesis of imides has been developed. In the presence of copper catalyst, N-benzylamideswere oxidized to the corresponding imides by TBHP/TEMPO system in moderate to good yields.
To understand lattice Boltzmann model capability for capturing nonequilibrium effects,the model with first-order expansion of the equilibrium distribution function is analytically investigated.In particular,the veloci...To understand lattice Boltzmann model capability for capturing nonequilibrium effects,the model with first-order expansion of the equilibrium distribution function is analytically investigated.In particular,the velocity profile of Couette flows is exactly obtained for the D2Q9 model,which shows retaining the first order expansion can capture rarefaction effects in the incompressible limit.Meanwhile,it clearly demonstrates that the D2Q9 model is not able to reflect flow characteristics in the Knudsen layer.展开更多
基金funded by the National Natural Science Foundation(61962009)the National Natural Science Foundation(62202118)+1 种基金Top Technology Talent Project from Guizhou Education Department(Qianjiao ji[2022]073)Foundation of Guangxi Key Laboratory of Cryptography and Information Security(GCIS202118).
文摘The data in Mobile Edge Computing(MEC)contains tremendousmarket value,and data sharing canmaximize the usefulness of the data.However,certain data is quite sensitive,and sharing it directly may violate privacy.Vertical Federated Learning(VFL)is a secure distributed machine learning framework that completes joint model training by passing encryptedmodel parameters rather than raw data,so there is no data privacy leakage during the training process.Therefore,the VFL can build a bridge between data demander and owner to realize data sharing while protecting data privacy.Typically,the VFL requires a third party for key distribution and decryption of training results.In this article,we employ the consortium blockchain instead of the traditional third party and design a VFL architecture based on the consortium blockchain for data sharing in MEC.More specifically,we propose a V-Raft consensus algorithm based on Verifiable Random Functions(VRFs),which is a variant of the Raft.The VRaft is able to elect leader quickly and stably to assist data demander and owner to complete data sharing by VFL.Moreover,we apply secret sharing todistribute the private key to avoid the situationwhere the training result cannot be decrypted if the leader crashes.Finally,we analyzed the performance of the V-Raft and carried out simulation experiments,and the results show that compared with Raft,the V-Raft has higher efficiency and better scalability.
文摘Using the lattice Boltzmann multiphase model,numerical simulations have been performed to understand the dynamics of droplet formation in a microfluidic cross-junction.The influence of capillary number,flow rate ratio,viscosity ratio,and viscosity of the continuous phase on droplet formation has been systematically studied over a wide range of capillary numbers.Two different regimes,namely the squeezinglike regime and the dripping regime,are clearly identified with the transition occurring at a critical capillary number Cacr.Generally,large flow rate ratio is expected to produce big droplets,while increasing capillary number will reduce droplet size.In the squeezing-like regime(Ca≤Cacr),droplet breakup process is dominated by the squeezing pressure and the viscous force;while in the dripping regime(Ca>Cacr),the viscous force is dominant and the droplet size becomes independent of the flow rate ratio as the capillary number increases.In addition,the droplet size weakly depends on the viscosity ratio in both regimes and decreases when the viscosity of the continuous phase increases.Finally,a scaling law is established to predict the droplet size.
文摘A novel and efficient approach to sulfonamides has been developed. Using TBHP as the oxidant and NH4I （20 mol%） as the catalyst, arylsulfonyl hydrazides reacted with amines to provide sulfonamides in moderate to good yields. Possible reaction pathway for the formation of the products was also discussed in this paper.
基金Financial support from Tongji University(20123231)is gratefully acknowledged.
文摘A new protocol for the synthesis of imides has been developed. In the presence of copper catalyst, N-benzylamideswere oxidized to the corresponding imides by TBHP/TEMPO system in moderate to good yields.
基金supported by the Engineering and Physical Sciences Research Council U.K.under Grants No.EP/F028865/1The research leading to these results has received the funding from the European Community’s Seventh Framework Programme FP7/2007-2013 under grant agreement ITN GASMEMS No.215504.
文摘To understand lattice Boltzmann model capability for capturing nonequilibrium effects,the model with first-order expansion of the equilibrium distribution function is analytically investigated.In particular,the velocity profile of Couette flows is exactly obtained for the D2Q9 model,which shows retaining the first order expansion can capture rarefaction effects in the incompressible limit.Meanwhile,it clearly demonstrates that the D2Q9 model is not able to reflect flow characteristics in the Knudsen layer.
