953 resultados para label switching


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We realize an end-to-end no-switching quantum key distribution protocol using continuous-wave coherent light. We encode weak broadband Gaussian modulations onto the amplitude and phase quadratures of light beams. Our no-switching protocol achieves high secret key rate via a post-selection protocol that utilizes both quadrature information simultaneously. We establish a secret key rate of 25 Mbits/s for a lossless channel and 1 kbit/s for 90% channel loss, per 17 MHz of detected bandwidth, assuming individual Gaussian eavesdropping attacks. Since our scheme is truly broadband, it can potentially deliver orders of magnitude higher key rates by extending the encoding bandwidth with higher-end telecommunication technology.

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Several host-adapted bacterial pathogens contain methyltransferases associated with type III restriction-modification (R-M) systems that are subject to reversible, high-frequency on/off switching of expression (phase variation). To investigate the role of phase-variable expression of R-M systems, we made a mutant strain lacking the methyltransferase (mod) associated with a type III R-M system of Haemophilus influenzae and analyzed its phenotype. By microarray analysis, we identified a number of genes that were either up- or down-regulated in the mod mutant strain. This system reports the coordinated random switching of a set of genes in a bacterial pathogen and may represent a widely used mechanism.

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The random switching of measurement bases is commonly assumed to be a necessary step of quantum key distribution protocols. In this paper we present a no-switching protocol and show that switching is not required for coherent-state continuous-variable quantum key distribution. Further, this protocol achieves higher information rates and a simpler experimental setup compared to previous protocols that rely on switching. We propose an optimal eavesdropping attack against this protocol, assuming individual Gaussian attacks. Finally, we investigate and compare the no-switching protocol applied to the original Bennett-Brassard 1984 scheme.

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Designer peptides have recently been developed as building blocks for novel self-assembled materials with stimuli-responsive properties. To date, such materials have been based on self-assembly in bulk aqueous solution or at solid-fluid interfaces. We have designed a 21-residue peptide, AM1, as a stimuli-responsive surfactant that switches molecular architectures at a fluid-fluid interface in response to changes in bulk aqueous solution composition. In the presence of divalent zinc at neutral pH, the peptide forms a mechanically strong 'film state'. In the absence of metal ions or at acid pH, the peptide adsorbs to form a mobile 'detergent state'. The two interfacial states can be actively and reversibly switched. Switching between the two states by a change in pH or the addition of a chelating agent leads to rapid emulsion coalescence or foam collapse. This work introduces a new class of surfactants that offer an environmentally friendly approach to control the stability of interfaces in foams, emulsions and fluid-fluid interfaces more generally.

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A new control algorithm using parallel braking resistor (BR) and serial fault current limiter (FCL) for power system transient stability enhancement is presented in this paper. The proposed control algorithm can prevent transient instability during first swing by immediately taking away the transient energy gained in faulted period. It can also reduce generator oscillation time and efficiently make system back to the post-fault equilibrium. The algorithm is based on a new system energy function based method to choose optimal switching point. The parallel BR and serial FCL resistor can be switched at the calculated optimal point to get the best control result. This method allows optimum dissipation of the transient energy caused by disturbance so to make system back to equilibrium in minimum time. Case studies are given to verify the efficiency and effectiveness of this new control algorithm.

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The deficiencies of stationary models applied to financial time series are well documented. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly appropriate for financial markets. We use a dynamic switching (modelled by a hidden Markov model) combined with a linear dynamical system in a hybrid switching state space model (SSSM) and discuss the practical details of training such models with a variational EM algorithm due to [Ghahramani and Hilton,1998]. The performance of the SSSM is evaluated on several financial data sets and it is shown to improve on a number of existing benchmark methods.