254 research outputs found
Diagnosis and Monitoring of Gingivitis in vivo Using Non-Invasive Technology - Infrared Spectroscopy
Peer reviewed: YesNRC publication: Ye
Virulence regulator AphB enhances toxR transcription in Vibrio cholerae
<p>Abstract</p> <p>Background</p> <p><it>Vibrio cholerae </it>is the causative agent of cholera. Extensive studies reveal that complicated regulatory cascades regulate expression of virulence genes, the products of which are required for <it>V. cholerae </it>to colonize and cause disease. In this study, we investigated the expression of the key virulence regulator ToxR under different conditions.</p> <p>Results</p> <p>We found that compared to that of wild type grown to stationary phase, the <it>toxR </it>expression was lower in an <it>aphB </it>mutant strain. AphB has been previously shown to be a key virulence regulator that is required to activate the expression of <it>tcpP</it>. When expressed constitutively, AphB is able to activate the <it>toxR </it>promoter. Furthermore, gel shift analysis indicates that AphB binds <it>toxR </it>promoter region directly. We also characterize the effect of AphB on the levels of the outer membrane porins OmpT and OmpU, which are known to be regulated by ToxR.</p> <p>Conclusions</p> <p>Our data indicate that <it>V. cholerae </it>possesses an additional regulatory loop that use AphB to activate the expression of two virulence regulators, ToxR and TcpP, which together control the expression of the master virulence regulator ToxT.</p
Entanglement Structure: Entanglement Partitioning in Multipartite Systems and Its Experimental Detection Using Optimizable Witnesses
Creating large-scale entanglement lies at the heart of many quantum
information processing protocols and the investigation of fundamental physics.
For multipartite quantum systems, it is crucial to identify not only the
presence of entanglement but also its detailed structure. This is because in a
generic experimental situation with sufficiently many subsystems involved, the
production of so-called genuine multipartite entanglement remains a formidable
challenge. Consequently, focusing exclusively on the identification of this
strongest type of entanglement may result in an all or nothing situation where
some inherently quantum aspects of the resource are overlooked. On the
contrary, even if the system is not genuinely multipartite entangled, there may
still be many-body entanglement present in the system. An identification of the
entanglement structure may thus provide us with a hint about where
imperfections in the setup may occur, as well as where we can identify groups
of subsystems that can still exhibit strong quantum-information-processing
capabilities. However, there is no known efficient methods to identify the
underlying entanglement structure. Here, we propose two complementary families
of witnesses for the identification of such structures. They are based on the
detection of entanglement intactness and entanglement depth, each requires only
the implementation of solely two local measurements. Our method is also robust
against noises and other imperfections, as reflected by our experimental
implementation of these tools to verify the entanglement structure of five
different eight-photon entangled states. We demonstrate how their entanglement
structure can be precisely and systematically inferred from the experimental
data. In achieving this goal, we also illustrate how the same set of data can
be classically postprocessed to learn the most about the measured system.Comment: 21 pages, 13 figure
Metropolitan all-pass and inter-city quantum communication network
We have demonstrated a metropolitan all-pass quantum communication network in
field fiber for four nodes. Any two nodes of them can be connected in the
network to perform quantum key distribution (QKD). An optical switching module
is presented that enables arbitrary 2-connectivity among output ports.
Integrated QKD terminals are worked out, which can operate either as a
transmitter, a receiver, or even both at the same time. Furthermore, an
additional link in another city of 60 km fiber (up to 130 km) is seamless
integrated into this network based on a trusted relay architecture. On all the
links, we have implemented protocol of decoy state scheme. All of necessary
electrical hardware, synchronization, feedback control, network software,
execution of QKD protocols are made by tailored designing, which allow a
completely automatical and stable running. Our system has been put into
operation in Hefei in August 2009, and publicly demonstrated during an
evaluation conference on quantum network organized by the Chinese Academy of
Sciences on August 29, 2009. Real-time voice telephone with one-time pad
encoding between any two of the five nodes (four all-pass nodes plus one
additional node through relay) is successfully established in the network
within 60km.Comment: 9 pages, 2 figures, 2 table
High speed self-testing quantum random number generation without detection loophole
Quantum mechanics provides means of generating genuine randomness that is
impossible with deterministic classical processes. Remarkably, the
unpredictability of randomness can be certified in a self-testing manner that
is independent of implementation devices. Here, we present an experimental
demonstration of self-testing quantum random number generation based on an
detection-loophole free Bell test with entangled photons. In the randomness
analysis, without the assumption of independent identical distribution, we
consider the worst case scenario that the adversary launches the most powerful
attacks against quantum adversary. After considering statistical fluctuations
and applying an 80 Gb 45.6 Mb Toeplitz matrix hashing, we achieve a
final random bit rate of 114 bits/s, with a failure probability less than
. Such self-testing random number generators mark a critical step
towards realistic applications in cryptography and fundamental physics tests.Comment: 34 pages, 10 figure
Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm
Based on data on the shear wave speed and physical properties of the shallow sediment samples collected in the northwest South China Sea, the hyperparameter selection and contribution of the characteristic factors of the machine learning model for predicting the shear wave speed of seafloor sediments were studied using the eXtreme Gradient Boosting (XGBoost) algorithm. An XGBoost model for predicting the shear wave speed of seafloor sediments was established based on four physical parameters of the sediments: porosity (n), water content (w), density (ρ), and average grain size (MZ). The result reveals that: (1) The shear wave speed has a good correlation with n, w, ρ, and MZ, and their Pearson correlation coefficients are all above 0.75, indicating that they can be used as the suitable characteristic parameters for predicting the shear wave speed based on the XGBoost model; (2) When the number of weak learners (n_estimators) is 115 and the maximum depth of the tree (max_depth) is 6, the XGBoost model has a very high goodness of fit (R2) of the validation data of 0.914, the very low mean absolute error (MAE) and mean absolute percentage error (MAPE) of the predicted shear wave speed are 3.366 m/s and 9.90%, respectively; (3) Compared with grain-shearing (GS) model and single- and dual-parameter regression equation prediction models, the XGBoost model for the shear wave speed of seafloor sediments has higher fitting goodness and lower prediction error
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