Nowadays, to utilize the abundant resources of cloud computing, most enterprise users prefer to store their big data on cloud servers for sharing and utilization. However, storing data in remote cloud servers is out of user's control and exposes to lots of security problems such data availability, unauthorized access and data integrity, among which data integrity is a challenging and urgent task in cloud computing. Many auditing schemes have been proposed to check the integrity of data in cloud, but these schemes usually have some disadvantages. One is that these auditing schemes cannot check which block is corrupt when the data is not integrated. The other is that there's no efficient authenticated data structure helping to achieve accurate auditing when the data needs to update frequently. To solve the problems, we propose a public auditing scheme for dynamic big data storage in cloud computing. Firstly, we design a dynamic index table, in which no elements need to be moved in insertion or deletion update operations. Secondly, when data in cloud is not integrated, the third-party auditor can detect which block is corrupt. Finally, an authorization is employed between the third party and cloud servers to prevent denial of service attack. The theoretical analysis and the simulation results demonstrate that our scheme is more secure and efficient.
This study aims to identify key environmental risk sources contributing to water eutrophication and to suggest certain risk management strategies for rural areas. The multi-angle indicators included in the risk source assessment system were non-point source pollution, deficient waste treatment, and public awareness of environmental risk, which combined psychometric paradigm methods, the contingent valuation method, and personal interviews to describe the environmental sensitivity of local residents. Total risk values of different villages near Taihu Lake were calculated in the case study, which resulted in a geographic risk map showing which village was the critical risk source of Taihu eutrophication. The increased application of phosphorus (P) and nitrogen (N), loss vulnerability of pollutant, and a lack of environmental risk awareness led to more serious non-point pollution, especially in rural China. Interesting results revealed by the quotient between the scores of objective risk sources and subjective risk sources showed what should be improved for each study village. More environmental investments, control of agricultural activities, and promotion of environmental education are critical considerations for rural environmental management. These findings are helpful for developing targeted and effective risk management strategies in rural areas.
Two chitin deacetylases, Cda1 and Cda2, from Coprinopsis cinerea were expressed and characterized. Cda1 preferably deacetylates the nonreducing end residue of (GlcNAc)2, the internal or nonreducing end residue of (GlcNAc)3 and the nonreducing residue of (GlcNAc)6 after deacetylating the internal residues. In contrast, Cda2 preferably deacetylates the reducing end residue of (GlcNAc)2, the internal or reducing end residue of (GlcNAc)3 and the reducing residue of (GlcNAc)6 after deacetylating the internal residues. Furthermore, Cda1 prefers chitohexaose with higher degrees of acetylation for deacetylation, while Cda2 shows a weaker preference for chitohexaose with varying degrees of acetylation. The predicted Cda1 structure shows more hydrophobic aromatic amino acids on the surface near subsite +1 in the active site than on the surface near subsite -1, whereas the predicted Cda2 structure has more hydrophobic aromatic amino acids on the surface near subsite -1 than on the surface near subsite +1, which may be the molecular basis of the distinctive catalytic features between Cda1 and Cda2. Notably, Cda1 has a high transcription level in the nonelongating basal stipe region, whereas Cda2 has a high transcription level in the elongating apical stipe region, and the transcription level of the former is approximately five times that of the latter. Correspondingly, the molar ratio of GlcN/GlcNAc increased from 0.15 in the cell wall of the apical stipe region to 0.22 in the cell wall of the basal stipe region. Different modes of action of Cda1 and Cda2 may be related to their functions in the different stipe regions.
Neuromorphic computing is a promising candidate for next-generation information technologies. In the present work, we report the realization of long-term plasticity and synapse emulations in Ag/SrTiO3/(La,Sr)MnO3 memristors with the SrTiO3 active layers down to 3 unit cells (u.c.) in thickness. In the 3 u.c.-thick SrTiO3 device, efficient control of Ag+-ion migration gives rise to enhanced memristive properties with the conductance continuously modulated within a large memory window of ∼26 000% between an Ohmic low resistance state (LRS) and an electron-tunneling high resistance state (HRS). In addition, long-term plasticity of the Ag/SrTiO3/(La,Sr)MnO3 memristors is found to be dependent upon the resistance state. In the HRS, the devices exhibit excellent spike-timing-dependent plasticity characteristics with a large modulation of synaptic weight of ∼3500% and sensitive response to electrical stimuli of as low as ∼1.0 V and as fast as ∼0.01 ms. Adopting the spike-timing-dependent plasticity results as database, supervised learning simulations are demonstrated in the Ag/SrTiO3/(La,Sr)MnO3-based neural networks and a high accuracy rate of 95.5% is achieved for recognizing handwritten digits. These results provide more insights into the ionic migration at nanoscale for continuous resistance modulation and facilitate the design of ultrathin memristors for high-density 3D stacking artificial neural networks.
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