LMS vs XMSS: Comparison of Stateful Hash-Based Signature Schemes on ARM Cortex-M4
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ABSTRACT:
SUBMITTER: Nitaj A
PROVIDER: S-EPMC7334983 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
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Project description:The transcriptional regulator Mga of Streptococcus pyogenes (the group A streptococcus, GAS) is known to directly activate several virulence genes important for colonization and immune evasion during exponential growth. Transcriptome analysis comparing two mga-1 serotypes (M1 SF370, M6 JRS4) and one mga-2 serotype (M4 GA40634) against their isogenic mga-inactivated strains uncovered a broader Mga regulon profile containing both activated and repressed genes with predicted functions primarily related to the uptake and metabolism of sugars. Although the divergent M1 and M4 Mga profiles were similar in size and content, the M6 JRS4 strain was clearly distinct, even from other M6 strains. Real-time RT-PCR and northern blot analysis validated our microarray results and confirmed that established core Mga regulon genes directly activated by Mga (emm, scpA, sof, fba) exhibited the highest activation levels across all strains tested. A novel ORF (Spy2036) encoding a cytosolic hypothetical protein was highly activated in all three serotypes and was called gene regulated by Mga or grm. Mga was shown to bind directly to Pgrm, which overlaps the Mga-regulated Psof in OF+ strains, suggesting that grm is part of the core Mga regulon and is able to activate two divergently transcribed genes from a single site in a class II background. Both class and serotype specific Mga-regulated genes, such as speB, were apparent. In fact, Mga activated speB as long as it was expressed in the wild type strain, although direct binding of Mga to the PspeB promoter could not be demonstrated. Thus, Mga is able to both directly and indirectly regulate genes shown to be important for virulence and the metabolic homeostasis of GAS. Keywords: Wild-type vs Mga-
2006-08-31 | GSE4597 | GEO
Project description:ObjectivesGenomic signatures like k-mers have become one of the most prominent approaches to describe genomic data. As a result, myriad real-world applications, such as the construction of de Bruijn graphs in genome assembly, have been benefited by recognizing genomic signatures. In other words, an efficient approach of genomic signature profiling is an essential need for tackling high-throughput sequencing reads. However, most of the existing approaches only recognize fixed-size k-mers while many research studies have shown the importance of considering variable-length k-mers.MethodsIn this paper, we present a novel genomic signature profiling approach, TahcoRoll, by extending the Aho-Corasick algorithm (AC) for the task of profiling variable-length k-mers. We first group nucleotides into two clusters and represent each cluster with a bit. The rolling hash technique is further utilized to encode signatures and read patterns for efficient matching.ResultsIn extensive experiments, TahcoRoll significantly outperforms the most state-of-the-art k-mer counters and has the capability of processing reads across different sequencing platforms on a budget desktop computer.ConclusionsThe single-thread version of TahcoRoll is as efficient as the eight-thread version of the state-of-the-art, JellyFish, while the eight-thread TahcoRoll outperforms the eight-thread JellyFish by at least four times.
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Project description:Recent rank-based attacks have reduced the security of Rainbow, which is one of the multi-layer UOV signatures, below the NIST security requirements by speeding up iterative kernel-finding operations using classical mathematics techniques. If quantum algorithms are applied to perform these iterative operations, the rank-based attacks may be more threatening to multi-layer UOV, including Rainbow. In this paper, we propose a quantum rectangular MinRank attack called the Q-rMinRank attack, the first quantum approach to key recovery attacks on multi-layer UOV signatures. Our attack is a general model applicable to multi-layer UOV signature schemes, and in this paper, we provide examples of its application to Rainbow and the Korean TTA standard, HiMQ. We design two quantum oracle circuits to find the kernel in consideration of the depth-width trade-off of quantum circuits. One is to reduce the width of the quantum circuits using qubits as a minimum, and the other is to reduce the depth using parallelization instead of using a lot of qubits. By designing quantum circuits to find kernels with fewer quantum resources and complexity by adding mathematical techniques, we achieve quadratic speedup for the MinRank attack to recover the private keys of multi-layer UOV signatures. We also estimate quantum resources for the designed quantum circuits and analyze quantum complexity based on them. The width-optimized circuit recovers the private keys of Rainbow parameter set V with only 1089 logical qubits. The depth-optimized circuit recovers the private keys of Rainbow parameter set V with a quantum complexity of 2174 , which is lower than the complexity of 2221 recovering the secret key of AES-192, which provides the same security level as parameter set III.
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Project description:Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.
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Project description:Code-based cryptography is one of few alternatives supposed to be secure in a post-quantum world. Meanwhile, identity-based identification and signature (IBI/IBS) schemes are two of the most fundamental cryptographic primitives, so several code-based IBI/IBS schemes have been proposed. However, with increasingly profound researches on coding theory, the security reduction and efficiency of such schemes have been invalidated and challenged. In this paper, we construct provably secure IBI/IBS schemes from code assumptions against impersonation under active and concurrent attacks through a provably secure code-based signature technique proposed by Preetha, Vasant and Rangan (PVR signature), and a security enhancement Or-proof technique. We also present the parallel-PVR technique to decrease parameter values while maintaining the standard security level. Compared to other code-based IBI/IBS schemes, our schemes achieve not only preferable public parameter size, private key size, communication cost and signature length due to better parameter choices, but also provably secure.
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Project description:Memristive switches are able to act as both storage and computing elements, which make them an excellent candidate for beyond-CMOS computing. In this paper, multi-input memristive switch logic is proposed, which enables the function X OR (Y NOR Z) to be performed in a single-step with three memristive switches. This ORNOR logic gate increases the capabilities of memristive switches, improving the overall system efficiency of a memristive switch-based computing architecture. Additionally, a computing system architecture and clocking scheme are proposed to further utilize memristive switching for computation. The system architecture is based on a design where multiple computational function blocks are interconnected and controlled by a master clock that synchronizes system data processing and transfer. The clocking steps to perform a full adder with the ORNOR gate are presented along with simulation results using a physics-based model. The full adder function block is integrated into the system architecture to realize a 64-bit full adder, which is also demonstrated through simulation.
| S-EPMC6787102 | biostudies-literature
Project description:BackgroundRecent technological advances have enabled high-throughput measurements of protein-protein interactions in the cell, producing large protein interaction networks for various species at an ever-growing pace. However, common technologies like yeast two-hybrid may experience high rates of false positive detection. To combat false positive discoveries, a number of different methods have been recently developed that associate confidence scores with protein interactions. Here, we perform a rigorous comparative analysis and performance assessment among these different methods.ResultsWe measure the extent to which each set of confidence scores correlates with similarity of the interacting proteins in terms of function, expression, pattern of sequence conservation, and homology to interacting proteins in other species. We also employ a new metric, the Signal-to-Noise Ratio of protein complexes embedded in each network, to assess the power of the different methods. Seven confidence assignment schemes, including those of Bader et al., Deane et al., Deng et al., Sharan et al., and Qi et al., are compared in this work.ConclusionAlthough the performance of each assignment scheme varies depending on the particular metric used for assessment, we observe that Deng et al. yields the best performance overall (in three out of four viable measures). Importantly, we also find that utilizing any of the probability assignment schemes is always more beneficial than assuming all observed interactions to be true or equally likely.
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Project description:Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback allows learning voluntary control over specific brain areas by means of operant conditioning and has been shown to decrease pain perception. To further increase the effect of rt-fMRI neurofeedback on pain, we directly compared two different target regions of the pain network, notably the anterior insular cortex (AIC) and the anterior cingulate cortex (ACC). Participants for this prospective study were randomly assigned to two age-matched groups of 14 participants each (7 females per group) for AIC and ACC feedback. First, a functional localizer using block-design heat pain stimulation was performed to define the pain-sensitive target region within the AIC or ACC. Second, subjects were asked to down-regulate the BOLD activation in four neurofeedback runs during identical pain stimulation. Data analysis included task-related and functional connectivity analysis. At the behavioral level, pain ratings significantly decreased during feedback vs. localizer runs, but there was no difference between AIC and ACC groups. Concerning neuroimaging, ACC and AIC showed consistent involvement of the caudate nucleus for subjects that learned down-regulation (17/28) in both task-related and functional connectivity analysis. The functional connectivity toward the caudate nucleus is stronger for the ACC while the AIC is more heavily connected to the ventrolateral prefrontal cortex. Consequently, the ACC and AIC are suitable targets for real-time fMRI neurofeedback during pain perception as they both affect the caudate nucleus, although functional connectivity indicates that the direct connection seems to be stronger with the ACC. Additionally, the caudate, an important area involved in pain perception and suppression, could be a good rt-fMRI target itself. Future studies are needed to identify parameters characterizing successful regulators and to assess the effect of repeated rt-fMRI neurofeedback on pain perception.
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Project description:Several sequence based genotyping schemes have been developed for Leptospira spp. The objective of this study was to genotype a collection of clinical and reference isolates using the two most commonly used schemes and compare and contrast the results.A total of 48 isolates consisting of L. interrogans (n?=?40) and L. kirschneri (n?=?8) were typed by the 7 locus MLST scheme described by Thaipadungpanit et al., and the 6 locus genotyping scheme described by Ahmed et al., (termed 7L and 6L, respectively). Two L. interrogans isolates were not typed using 6L because of a deletion of three nucleotides in lipL32. The remaining 46 isolates were resolved into 21 sequence types (STs) by 7L, and 30 genotypes by 6L. Overall nucleotide diversity (based on concatenated sequence) was 3.6% and 2.3% for 7L and 6L, respectively. The D value (discriminatory ability) of 7L and 6L were comparable, i.e. 92.0 (95% CI 87.5-96.5) vs. 93.5 (95% CI 88.6-98.4). The dN/dS ratios calculated for each locus indicated that none were under positive selection. Neighbor joining trees were reconstructed based on the concatenated sequences for each scheme. Both trees showed two distinct groups corresponding to L. interrogans and L. kirschneri, and both identified two clones containing 10 and 7 clinical isolates, respectively. There were six instances in which 6L split single STs as defined by 7L into closely related clusters. We noted two discrepancies between the trees in which the genetic relatedness between two pairs of strains were more closely related by 7L than by 6L.This genetic analysis indicates that the two schemes are comparable. We discuss their practical advantages and disadvantages.
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Project description:Only a small proportion of pharmaceuticals available for commercial use have been monitored in the aquatic environment, and even less is known about the effects on organisms. With thousands of pharmaceuticals in use, it is not feasible to monitor or assess the effects of all of these compounds. Prioritisation schemes allow the ranking of pharmaceuticals based on their potential as environmental contaminants, allowing resources to be appropriately used on those which are most likely to enter the environment and cause greatest harm. Many different types of prioritisation schemes exist in the literature and those utilising predicted environmental concentrations (PECs), the fish plasma model (FPM), critical environmental concentrations (CECs) and acute ecotoxicological data were assessed in the current study using the 50 most prescribed drugs in the UK. PECs were found to be overestimates of mean measured environmental concentrations but mainly underestimations of maximum concentrations. Acute ecological data identified different compounds of concern to the other effects assessments although the FPM and CECs methods were more conservative. These schemes highlighted antidepressants, lipid regulators, antibiotics, antihypertensive compounds and ibuprofen as priority compounds for further study and regulation.
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