In this study, the efects of various methods of washing and drying of MOF-5 nanocrystals on structure formation were investigated. Eight samples of MOF-5 were synthesized under diferent conditions. TGA, XRD and PSD an...In this study, the efects of various methods of washing and drying of MOF-5 nanocrystals on structure formation were investigated. Eight samples of MOF-5 were synthesized under diferent conditions. TGA, XRD and PSD analysis were applied to characterize of the samples. The methods of washing and drying were found to be important in determining the final structure of MOF-5s. MOF-5 with high BET surface area can be obtained by choosing a suitable method of washing and drying. According to the results obtained in this work, it was found that vacuum drying at 425℃ is sufcient to dissolve the MOF-5-DMF. Similar results were obtained by washing method（withCH2Cl2 andCHCl3）, when compared with vacuum drying at 425℃ according to XRD test. The pore size distribution of samples 1-5 and 8 were calculated by SHN1 method and results showed that the samples in which solvent vacuum was DMF, have lower pore volume, uniform pore size distribution and the pore size are smaller than samples 3, 4 and 8. It was also found that activated MOF-5 can be converted to its deactivated form prior to drying of the samples.展开更多
We consider the systematics of α-decay half-lives of super-heavy nuclei versus the decay energy and the total α-kinetic energy. We calculate the half-lives using the experimental Qα values. The computed half-lives ...We consider the systematics of α-decay half-lives of super-heavy nuclei versus the decay energy and the total α-kinetic energy. We calculate the half-lives using the experimental Qα values. The computed half-lives are compared with the experimental data and with existing empirical estimates and are found to be in good agreement. Also, we obtain α-preformation factors from the ratio between theoretical and experimental results for some super- heavy nuclei and evaluate the standard deviation. The results indicate the acceptability of the approach.展开更多
The popularization of intelligent healthcare devices and big data analytics significantly boosts the development of Smart Healthcare Networks(SHNs).To enhance the precision of diagnosis,different participants in SHNs ...The popularization of intelligent healthcare devices and big data analytics significantly boosts the development of Smart Healthcare Networks(SHNs).To enhance the precision of diagnosis,different participants in SHNs share health data that contain sensitive information.Therefore,the data exchange process raises privacy concerns,especially when the integration of health data from multiple sources(linkage attack)results in further leakage.Linkage attack is a type of dominant attack in the privacy domain,which can leverage various data sources for private data mining.Furthermore,adversaries launch poisoning attacks to falsify the health data,which leads to misdiagnosing or even physical damage.To protect private health data,we propose a personalized differential privacy model based on the trust levels among users.The trust is evaluated by a defined community density,while the corresponding privacy protection level is mapped to controllable randomized noise constrained by differential privacy.To avoid linkage attacks in personalized differential privacy,we design a noise correlation decoupling mechanism using a Markov stochastic process.In addition,we build the community model on a blockchain,which can mitigate the risk of poisoning attacks during differentially private data transmission over SHNs.Extensive experiments and analysis on real-world datasets have testified the proposed model,and achieved better performance compared with existing research from perspectives of privacy protection and effectiveness.展开更多
文摘In this study, the efects of various methods of washing and drying of MOF-5 nanocrystals on structure formation were investigated. Eight samples of MOF-5 were synthesized under diferent conditions. TGA, XRD and PSD analysis were applied to characterize of the samples. The methods of washing and drying were found to be important in determining the final structure of MOF-5s. MOF-5 with high BET surface area can be obtained by choosing a suitable method of washing and drying. According to the results obtained in this work, it was found that vacuum drying at 425℃ is sufcient to dissolve the MOF-5-DMF. Similar results were obtained by washing method（withCH2Cl2 andCHCl3）, when compared with vacuum drying at 425℃ according to XRD test. The pore size distribution of samples 1-5 and 8 were calculated by SHN1 method and results showed that the samples in which solvent vacuum was DMF, have lower pore volume, uniform pore size distribution and the pore size are smaller than samples 3, 4 and 8. It was also found that activated MOF-5 can be converted to its deactivated form prior to drying of the samples.
文摘We consider the systematics of α-decay half-lives of super-heavy nuclei versus the decay energy and the total α-kinetic energy. We calculate the half-lives using the experimental Qα values. The computed half-lives are compared with the experimental data and with existing empirical estimates and are found to be in good agreement. Also, we obtain α-preformation factors from the ratio between theoretical and experimental results for some super- heavy nuclei and evaluate the standard deviation. The results indicate the acceptability of the approach.
基金supported by the National Key Research and Development Program of China(No.2021YFF0900400).
文摘The popularization of intelligent healthcare devices and big data analytics significantly boosts the development of Smart Healthcare Networks(SHNs).To enhance the precision of diagnosis,different participants in SHNs share health data that contain sensitive information.Therefore,the data exchange process raises privacy concerns,especially when the integration of health data from multiple sources(linkage attack)results in further leakage.Linkage attack is a type of dominant attack in the privacy domain,which can leverage various data sources for private data mining.Furthermore,adversaries launch poisoning attacks to falsify the health data,which leads to misdiagnosing or even physical damage.To protect private health data,we propose a personalized differential privacy model based on the trust levels among users.The trust is evaluated by a defined community density,while the corresponding privacy protection level is mapped to controllable randomized noise constrained by differential privacy.To avoid linkage attacks in personalized differential privacy,we design a noise correlation decoupling mechanism using a Markov stochastic process.In addition,we build the community model on a blockchain,which can mitigate the risk of poisoning attacks during differentially private data transmission over SHNs.Extensive experiments and analysis on real-world datasets have testified the proposed model,and achieved better performance compared with existing research from perspectives of privacy protection and effectiveness.
