45,762 research outputs found

    Efficient identity-based broadcast encryption without random oracles.

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    We propose a new efficient identity-based broadcast encryption scheme without random oracles and prove that it achieves selective identity, chosen plaintext security. Our scheme is constructed based on bilinear Diffie-Hellman inversion assumption and it is a good efficient hybrid encryption scheme, which achieves O(1)-size ciphertexts, public parameters and constant size private keys. In our scheme, either ciphertexts or public parameters has no relation with the number of receivers, moreover, both the encryption and decryption only require one pairing computation. Compared with other identity-based broadcast encryption schemes, our scheme has comparable properties, but with a better efficiency

    An Efficient Method for GPS Multipath Mitigation Using the Teager-Kaiser-Operator-based MEDLL

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    An efficient method for GPS multipath mitigation is proposed. The motivation for this proposed method is to integrate the Teager-Kaiser Operator (TKO) with the Multipath Estimating Delay Lock Loop (MEDLL) module to mitigate the GPS multipath efficiently. The general implementation process of the proposed method is that we first utilize the TKO to operate on the received signal’s Auto-Correlation Function (ACF) to get an initial estimate of the multipaths. Then we transfer the initial estimated results to the MEDLL module for a further estimation. Finally, with a few iterations which are less than those of the original MEDLL algorithm, we can get a more accurate estimate of the Line-Of-Sight (LOS) signal, and thus the goal of the GPS multipath mitigation is achieved. The simulation results show that compared to the original MEDLL algorithm, the proposed method can reduce the computation load and the hardware and/or software consumption of the MEDLL module, meanwhile, without decreasing the algorithm accuracy

    Tick-borne encephalitis virus induces chemokine RANTES expression via activation of IRF-3 pathway.

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    BACKGROUND: Tick-borne encephalitis virus (TBEV) is one of the most important flaviviruses that targets the central nervous system (CNS) and causes encephalitides in humans. Although neuroinflammatory mechanisms may contribute to brain tissue destruction, the induction pathways and potential roles of specific chemokines in TBEV-mediated neurological disease are poorly understood. METHODS: BALB/c mice were intracerebrally injected with TBEV, followed by evaluation of chemokine and cytokine profiles using protein array analysis. The virus-infected mice were treated with the CC chemokine antagonist Met-RANTES or anti-RANTES mAb to determine the role of RANTES in affecting TBEV-induced neurological disease. The underlying signaling mechanisms were delineated using RANTES promoter luciferase reporter assay, siRNA-mediated knockdown, and pharmacological inhibitors in human brain-derived cell culture models. RESULTS: In a mouse model, pathological features including marked inflammatory cell infiltrates were observed in brain sections, which correlated with a robust up-regulation of RANTES within the brain but not in peripheral tissues and sera. Antagonizing RANTES within CNS extended the survival of mice and reduced accumulation of infiltrating cells in the brain after TBEV infection. Through in vitro studies, we show that virus infection up-regulated RANTES production at both mRNA and protein levels in human brain-derived cell lines and primary progenitor-derived astrocytes. Furthermore, IRF-3 pathway appeared to be essential for TBEV-induced RANTES production. Site mutation of an IRF-3-binding motif abrogated the RANTES promoter activity in virus-infected brain cells. Moreover, IRF-3 was activated upon TBEV infection as evidenced by phosphorylation of TBK1 and IRF-3, while blockade of IRF-3 activation drastically reduced virus-induced RANTES expression. CONCLUSIONS: Our findings together provide insights into the molecular mechanism underlying RANTES production induced by TBEV, highlighting its potential importance in the process of neuroinflammatory responses to TBEV infection

    The Universal Edge Physics in Fractional Quantum Hall Liquids

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    The chiral Luttinger liquid theory for fractional quantum Hall edge transport predicts universal power-law behavior in the current-voltage (II-VV) characteristics for electrons tunneling into the edge. However, it has not been unambiguously observed in experiments in two-dimensional electron gases based on GaAs/GaAlAs heterostructures or quantum wells. One plausible cause is the fractional quantum Hall edge reconstruction, which introduces non-chiral edge modes. The coupling between counterpropagating edge modes can modify the exponent of the II-VV characteristics. By comparing the ν=1/3\nu=1/3 fractional quantum Hall states in modulation-doped semiconductor devices and in graphene devices, we show that the graphene-based systems have an experimental accessible parameter region to avoid the edge reconstruction, which is suitable for the exploration of the universal edge tunneling exponent predicted by the chiral Luttinger liquid theory.Comment: 7 pages, 6 figure

    Measurement of the c-axis optical reflectance of AFe2_2As2_2 (A=Ba, Sr) single crystals: Evidence of different mechanisms for the formation of two energy gaps

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    We present the c-axis optical reflectance measurement on single crystals of BaFe2_2As2_2 and SrFe2_2As2_2, the parent compounds of FeAs based superconductors. Different from the ab-plane optical response where two distinct energy gaps were observed in the SDW state, only the smaller energy gap could be seen clearly for \textbf{E}\parallelc-axis. The very pronounced energy gap structure seen at a higher energy scale for \textbf{E}\parallelab-plane is almost invisible. We propose a novel picture for the band structure evolution across the SDW transition and suggest different driving mechanisms for the formation of the two energy gaps.Comment: 4 page

    Mathematical control of complex systems 2013

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    Mathematical control of complex systems have already become an ideal research area for control engineers, mathematicians, computer scientists, and biologists to understand, manage, analyze, and interpret functional information/dynamical behaviours from real-world complex dynamical systems, such as communication systems, process control, environmental systems, intelligent manufacturing systems, transportation systems, and structural systems. This special issue aims to bring together the latest/innovative knowledge and advances in mathematics for handling complex systems. Topics include, but are not limited to the following: control systems theory (behavioural systems, networked control systems, delay systems, distributed systems, infinite-dimensional systems, and positive systems); networked control (channel capacity constraints, control over communication networks, distributed filtering and control, information theory and control, and sensor networks); and stochastic systems (nonlinear filtering, nonparametric methods, particle filtering, partial identification, stochastic control, stochastic realization, system identification)
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