A Secure and Fast Dispersal Storage Scheme Based on the Learning with Errors Problem

Data confidentiality and availability are of primary concern in data storage. Dispersal storage schemes achieve these two security properties by transforming the data into multiple codewords and dispersing them across multiple storage servers. Existing schemes achieve confidentiality and availability by various cryptographic and coding algorithms, but only under the assumption that an adversary cannot obtain more than a certain number of codewords. Meanwhile existing schemes are designed for storing archives. In this paper, we propose a novel dispersal storage scheme based on the learning with errors problem, known as storage with errors (SWE). SWE can resist even more powerful adversaries. Besides, SWE favorably supports dynamic data operations that are both efficient and secure, which is more practical for cloud storage. Furthermore, SWE achieves security at relatively low computational overhead, but the same storage cost compared with the state of the art. We also develop a prototype to validate and evaluate SWE. Analysis and experiments show that with proper configurations, SWE outperforms existing schemes in encoding/decoding speed

Tests on the Accuracy and Scalability of the Full-Potential DFT Method Based on Multiple Scattering Theory

We investigate a reduced scaling full-potential DFT method based on the multiple scattering theory (MST) code MuST, which is released online (https://github.com/mstsuite/MuST) very recently. First, we test the accuracy by calculating structural properties of typical body-centered cubic (BCC) metals (V, Nb, and Mo). It is shown that the calculated lattice parameters, bulk moduli, and elastic constants agree with those obtained from the VASP, WIEN2k, EMTO, and Elk codes. Second, we test the locally self-consistent multiple scattering (LSMS) mode, which achieves reduced scaling by neglecting the multiple scattering processes beyond a cut-off radius. In the case of Nb, the accuracy of 0.5 mRy/atom can be achieved with a cut-off radius of 20 Bohr, even when small deformations are imposed on the lattice. Despite that the calculation of valence states based on MST exhibits linear scaling, the whole computational procedure has an overall scaling of about O(N-1.6), due to the fact that the updating of Coulomb potential scales almost as O(N-2). Nevertheless, it can be still expected that MuST would provide a reliable and accessible way to large-scale first-principles simulations of metals and alloys

Torsion Dependence of Domain Transition and MI Effect of Melt-Extracted Co68.15Fe4.35Si12.25B13.25Nb1Cu1 Microwires

We present the torsional stress induced magnetoimpedance (MI) effect and surface domain structure evolution of magnetostrictive melt-extracted Co68.15Fe4.35Si12.25B13.25Nb1Cu1 microwires. Experimental results indicate that the surface domain structures observed by magnetic force microscope (MFM) transform from the weak circumferential domain of as-cast state to the helical domain under large torsional strain of 81.6 (2π rad/m). Domain wall movement distorts at torsional strain ξ=20.4 (2π rad/m) and forms a helical anisotropy with an angle of around 30° versus axial direction of wire. At 15 MHz, the maximum of GMI ratio ΔZ/Z(%) increases to 194.4% at ξ=20.4 (2π rad/m) from 116.3% of the as-cast state and then decreases to 134.9% at ξ=102.0 (2π rad/m). The torsion magnetoimpedance (TMI) ratio ΔZ/Zξ(%) is up to 290%. Based on this large torsional strain and high MI ratio, the microwire can be as an referred candidate for high-performance TMI sensor application

Principles of Inter-Amino-Acid Recognition Revealed by Binding Energies between Homogeneous Oligopeptides.

We have determined the interaction strengths of the common naturally occurring amino acids using a complete binding affinity matrix of 20 × 20 pairs of homo-octapeptides consisting of the 20 common amino acids between stationary and mobile states. We used a bead-based fluorescence assay for these measurements. The results provide a basis for analyzing specificity, polymorphisms, and selectivity of inter-amino-acid interactions. Comparative analyses of the binding energies, i.e., the free energies of association (ΔG A), reveal contributions assignable to both main-chain-related and side-chain-related interactions originating from the chemical structures of these 20 common amino acids. Side-chain-side-chain and side-chain-main-chain interactions are found to be pronounced in an identified set of amino acid pairs that determine the basis of inter-amino-acid recognition

Principles of Inter-Amino-Acid Recognition Revealed by Binding Energies between Homogeneous Oligopeptides.

We have determined the interaction strengths of the common naturally occurring amino acids using a complete binding affinity matrix of 20 × 20 pairs of homo-octapeptides consisting of the 20 common amino acids between stationary and mobile states. We used a bead-based fluorescence assay for these measurements. The results provide a basis for analyzing specificity, polymorphisms, and selectivity of inter-amino-acid interactions. Comparative analyses of the binding energies, i.e., the free energies of association (ΔG A), reveal contributions assignable to both main-chain-related and side-chain-related interactions originating from the chemical structures of these 20 common amino acids. Side-chain-side-chain and side-chain-main-chain interactions are found to be pronounced in an identified set of amino acid pairs that determine the basis of inter-amino-acid recognition

Principles of Inter-Amino-Acid Recognition Revealed by Binding Energies between Homogeneous Oligopeptides

We have determined the interaction strengths of the common naturally occurring amino acids using a complete binding affinity matrix of 20 × 20 pairs of homo-octapeptides consisting of the 20 common amino acids between stationary and mobile states. We used a bead-based fluorescence assay for these measurements. The results provide a basis for analyzing specificity, polymorphisms, and selectivity of inter-amino-acid interactions. Comparative analyses of the binding energies, i.e., the free energies of association (ΔGA), reveal contributions assignable to both main-chain-related and side-chain-related interactions originating from the chemical structures of these 20 common amino acids. Side-chain–side-chain and side-chain–main-chain interactions are found to be pronounced in an identified set of amino acid pairs that determine the basis of inter-amino-acid recognition