Magnetic particle imaging (MPI) is a radiation-free vessel- and target-imaging modality that can sensitively detect nanoparticles. A static magnetic gradient field, referred to as a selection field, is required in MPI to provide a field-free region (FFR) for spatial encoding. The image resolution of MPI is closely related to the size of the FFR, which is determined by the selection field gradient amplitude. Because of the limitations of existing gradient coil hardware, the image resolution of MPI cannot satisfy the clinical requirements of human in vivo imaging. Pulsed excitation has been confirmed to improve the image resolution of MPI by breaking down the 'relaxation wall.' This work proposes the use of a pulsed waveform magnetic gradient from magnetic resonance imaging to further improve the image resolution of MPI. Through alignment of the gradient direction along the field-free line (FFL), each location on the FFL is able to have a unique excitation field strength that generates a specific relaxation-induced decay signal. Through excitation of nanoparticles on the FFL with many gradient profiles, a high-resolution, one-dimensional (1D) image can be reconstructed on the FFL. For larger magnetic nanoparticles, simulation results revealed that a pulsed excitation field with a greater flat portion generates a 1D bar pattern phantom image with a higher correlation and spatial resolution. With parallel FFL and gradient coil movements, high-resolution, two-dimensional (2D) Shepp-Logan phantom and brain vessel maps were reconstructed through repetition of the spatially resolved measurement of magnetic nanoparticles on the FFL.

Direct Anonymous Attestation (DAA) is an anonymous signature scheme, which allows the Trusted Platform Module (TPM), a small chip embedded in a host computer, to attest to the state of the host system, while preserving the privacy of the user. DAA provides two signature modes: fully anonymous signatures and pseudonymous signatures. One main goal of designing DAA schemes is to reduce the TPM signing workload as much as possible, as the TPM has only limited resources. In an optimal DAA scheme, the signing workload on the TPM will be no more than that required for a normal signature like ECSchnorr. To date, no scheme has achieved the optimal signing efficiency for both signature modes. In this paper, we propose the first DAA scheme which achieves the optimal TPM signing efficiency for both signature modes. In this scheme, the TPM takes only a single exponentiation to generate a signature, and this single exponentiation can be pre-computed. Our scheme can be implemented using the existing TPM 2.0 commands, and thus is compatible with the TPM 2.0 specification. We benchmarked the TPM 2.0 commands needed for three DAA use cases on an Infineon TPM 2.0 chip, and also implemented the host signing and verification algorithm for our DAA scheme on a laptop with 1.80GHz Intel Core i7-8550U CPU. Our experimental results show that our DAA scheme obtains a total signing time of about 144 ms for either signature mode, while with pre-computation we can obtain a signing time of about 65 ms. Based on our benchmark results for the pseudonymous signature mode, our scheme is roughly$2\times $(resp.,$5\times $) faster than the existing DAA schemes supported by TPM 2.0 in terms of total (resp., online) signing efficiency.

BACKGROUND: Genome-wide miRNA expression data can be used to study miRNA dysregulation comprehensively. Although many open-source tools for microRNA (miRNA)-seq data analyses are available, challenges remain in accurate miRNA quantification from large-scale miRNA-seq dataset. We implemented a pipeline called QuickMIRSeq for accurate quantification of known miRNAs and miRNA isoforms (isomiRs) from multiple samples simultaneously. RESULTS: QuickMIRSeq considers the unique nature of miRNAs and combines many important features into its implementation. First, it takes advantage of high redundancy of miRNA reads and introduces joint mapping of multiple samples to reduce computational time. Second, it incorporates the strand information in the alignment step for more accurate quantification. Third, reads potentially arising from background noise are filtered out to improve the reliability of miRNA detection. Fourth, sequences aligned to miRNAs with mismatches are remapped to a reference genome to further reduce false positives. Finally, QuickMIRSeq generates a rich set of QC metrics and publication-ready plots. CONCLUSIONS: The rich visualization features implemented allow end users to interactively explore the results and gain more insights into miRNA-seq data analyses. The high degree of automation and interactivity in QuickMIRSeq leads to a substantial reduction in the time and effort required for miRNA-seq data analysis.

In this paper, we built LSWC database in time series from 2002 to 2015 derived from AMSR-E, Windsat and AMSR2 to detect flood events. Then, by conducting spatio-temporal analysis we made clear the flooding pattern and dug up some regularity, hidden information of flooding in different land use land cover situation based on viewpoint of retrieval of historical global record. Last, PALSAR data was used to conduct more precise calibration of AMSR-E by establishing a calibration function of index NDFI, NDPI with PALSAR LSWC. It shows a good relationship between these indexes. Thus, the availability and importance of LSWC database for flooding detection on global scale was indicated.

Abstract The new released trusted platform module (TPM) specification, TPM2.0, adds cryptographic support for key exchange by providing SM2 authenticated key exchange (AKE) application programming interface (API) commands. Xu analyzed the SM2 AKE protocol and found that it was insecure in common computing environment by presenting two types of unknown key share attacks. Here, we present another design weakness of the SM2 AKE protocol, which might cause that the protocol cannot be proven secure in modern security models. We also analyze the security of SM2 AKE protocol in TPM2.0, whose running environment is very different and find that (i) it indeed gets some security improvements through the protection capability provided by the two SM2 AKE commands of TPM2.0 but (ii) it still has some weaknesses, which might lead to unknown key share and key‐compromise impersonation attacks because of the bad design of the TPM2.0 application programming interface. We solve the weaknesses of SM2 AKE protocol in TPM2.0 by slightly modifying one SM2 AKE command and finally give a formal proof of our solution in the Canetti and Krawczyk model. Our work shows that TPM2.0 could provide a proven secure SM2 AKE by slightly modifying one command. Copyright © 2014 John Wiley & Sons, Ltd.

Direct Anonymous Attestation (DAA) is a signature scheme that provides a balance between user privacy and authentication in a reasonable way. The first RSA-based DAA is proposed in 2004, since then several ECC-based DAA schemes are proposed to achieve better performance. To analyze DAA schemes from a practical point of view, it is necessary to consider implementation-related issues, such as elliptic curve selection and runtime performance. We present a framework for implementing and evaluating various DAA schemes for multiple computing platforms. We implement four DAA schemes using different elliptic curves and show detailed performance evaluation for both PC and mobile device. We analyze the impact of elliptic selections on the performance of DAA schemes and propose practical techniques such as pre-computation to improve the performance of DAA schemes. We also discuss revocation of DAA and present a novel technique which significantly reduces the time of privacy-enhanced signature revocation, thus making privacy-enhanced revocation practical even for embedded mobile devices.