A phenomenon of shock wave reacceleration was studied when Ti＋Si reactive powder is loaded by a high-speed flyer.The self-propagating reaction in the Ti＋Si reactive powder was triggered by the high speed impaction o...A phenomenon of shock wave reacceleration was studied when Ti＋Si reactive powder is loaded by a high-speed flyer.The self-propagating reaction in the Ti＋Si reactive powder was triggered by the high speed impaction of the flyer launched by a two-stage gas gun.In the process of self-propagating reaction,a strand of optical fiber and the electric pins were used to measure the velocity of shock wave propagation.The experimental results showed that the initial velocity of shock wave in the reactive powder was a few hundred meters per second,and then it decreased obviously with the increase of propagation distance.This phenomenon was also verified in the process of a pure Si powder loaded by a shock,while the phenomenon of shock wave reacceleration was not observed in the Ti＋Si reactive powder.展开更多
Blockchain platform Ethereum has involved millions of accounts due to its strong potential for providing numerous services based on smart contracts.These massive accounts can be divided into diverse categories,such as...Blockchain platform Ethereum has involved millions of accounts due to its strong potential for providing numerous services based on smart contracts.These massive accounts can be divided into diverse categories,such as miners,tokens,and exchanges,which is termed as account diversity in this paper.The benefit of investigating diversity are multi-fold,including understanding the Ethereum ecosystem deeper and opening the possibility of tracking certain abnormal activities.Unfortunately,the exploration of blockchain account diversity remains scarce.Even the most relevant studies,which focus on the deanonymization of the accounts on Bitcoin,can hardly be applied on Ethereum since their underlying protocols and user idioms are different.To this end,we present the first attempt to demystify the account diversity on Ethereum.The key observation is that different accounts exhibit diverse behavior patterns,leading us to propose the heuristics for classification as the premise.We then raise the coverage rate of classification by the statistical learning model Maximum Likelihood Estimation(MLE).We collect real-world data through extensive efforts to evaluate our proposed method and show its effectiveness.Furthermore,we make an in-depth analysis of the dynamic evolution of the Ethereum ecosystem and uncover the abnormal arbitrage actions.As for the former,we validate two sweeping statements reliably:(1)standalone miners are gradually replaced by the mining pools and cooperative miners;(2)transactions related to the mining pool and exchanges take up a large share of the total transactions.The latter analysis shows that there are a large number of arbitrage transactions transferring the coins from one exchange to another to make a price difference.展开更多
基金Supported by the National Natural Science Foundation of China(11172043)
文摘A phenomenon of shock wave reacceleration was studied when Ti＋Si reactive powder is loaded by a high-speed flyer.The self-propagating reaction in the Ti＋Si reactive powder was triggered by the high speed impaction of the flyer launched by a two-stage gas gun.In the process of self-propagating reaction,a strand of optical fiber and the electric pins were used to measure the velocity of shock wave propagation.The experimental results showed that the initial velocity of shock wave in the reactive powder was a few hundred meters per second,and then it decreased obviously with the increase of propagation distance.This phenomenon was also verified in the process of a pure Si powder loaded by a shock,while the phenomenon of shock wave reacceleration was not observed in the Ti＋Si reactive powder.
基金supported by Key-Area Rescearch and Development Program of Guangdong Province(2020B010109005)the National Natural Science Foundation of China(Grant No.62072197)。
文摘Blockchain platform Ethereum has involved millions of accounts due to its strong potential for providing numerous services based on smart contracts.These massive accounts can be divided into diverse categories,such as miners,tokens,and exchanges,which is termed as account diversity in this paper.The benefit of investigating diversity are multi-fold,including understanding the Ethereum ecosystem deeper and opening the possibility of tracking certain abnormal activities.Unfortunately,the exploration of blockchain account diversity remains scarce.Even the most relevant studies,which focus on the deanonymization of the accounts on Bitcoin,can hardly be applied on Ethereum since their underlying protocols and user idioms are different.To this end,we present the first attempt to demystify the account diversity on Ethereum.The key observation is that different accounts exhibit diverse behavior patterns,leading us to propose the heuristics for classification as the premise.We then raise the coverage rate of classification by the statistical learning model Maximum Likelihood Estimation(MLE).We collect real-world data through extensive efforts to evaluate our proposed method and show its effectiveness.Furthermore,we make an in-depth analysis of the dynamic evolution of the Ethereum ecosystem and uncover the abnormal arbitrage actions.As for the former,we validate two sweeping statements reliably:(1)standalone miners are gradually replaced by the mining pools and cooperative miners;(2)transactions related to the mining pool and exchanges take up a large share of the total transactions.The latter analysis shows that there are a large number of arbitrage transactions transferring the coins from one exchange to another to make a price difference.
