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 $\times$ 45.6 Mb Toeplitz matrix hashing, we achieve a final random bit rate of 114 bits/s, with a failure probability less than $10^{-5}$. 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