An Infrared study of the Josephson vortex state in high-Tc cuprates

We report the results of the c-axis infrared spectroscopy of La_{2-x} Sr_x CuO_4 in high magnetic field oriented parallel to the CuO_2 planes. A significant suppression of the superfluid density with magnetic field rho_s(H) is observed for both underdoped (x=0.125) and overdoped (x=0.17) samples. We show that the existing theoretical models of the Josephson vortex state fail to consistently describe the observed effects and discuss possible reasons for the discrepancies

The origin of flux-flow resistance oscillations in BiSrCaCuO: Fiske steps in a single junction?

We propose an alternative explanation to the oscillations of the flux-flow resistance found in several previously published experiments with BiSrCaCuO stacks. It has been argued by the previous authors that the period of the oscillations corresponding to the field needed to add one vortex per two intrinsic Josephson junctions is associated with a moving triangular lattice of vortices (out-of-phase mode), while the period corresponding to one vortex per one junction is due to the square lattice (in-phase mode). In contrast, we show that both type of oscillations may occur in a single-layer Josephson junction and thus the above interpretation is inconsistent

Stochastic transitions of attractors in associative memory models with correlated noise

We investigate dynamics of recurrent neural networks with correlated noise to analyze the noise's effect. The mechanism of correlated firing has been analyzed in various models, but its functional roles have not been discussed in sufficient detail. Aoyagi and Aoki have shown that the state transition of a network is invoked by synchronous spikes. We introduce two types of noise to each neuron: thermal independent noise and correlated noise. Due to the effects of correlated noise, the correlation between neural inputs cannot be ignored, so the behavior of the network has sample dependence. We discuss two types of associative memory models: one with auto- and weak cross-correlation connections and one with hierarchically correlated patterns. The former is similar in structure to Aoyagi and Aoki's model. We show that stochastic transition can be presented by correlated rather than thermal noise. In the latter, we show stochastic transition from a memory state to a mixture state using correlated noise. To analyze the stochastic transitions, we derive a macroscopic dynamic description as a recurrence relation form of a probability density function when the correlated noise exists. Computer simulations agree with theoretical results.Comment: 21 page

Josephson Coupling, Phase Correlations, and Josephson Plasma Resonance in Vortex Liquid Phase

Josephson plasma resonance has been introduced recently as a powerful tool to probe interlayer Josephson coupling in different regions of the vortex phase diagram in layered superconductors. In the liquid phase, the high temperature expansion with respect to the Josephson coupling connects the Josephson plasma frequency with the phase correlation function. This function, in turn, is directly related to the pair distribution function of the liquid. We develop a recipe to extract the phase and density correlation functions from the dependencies of the plasma resonance frequency $\omega_p({\bf B})$ and the $c$ axis conductivity $\sigma_c({\bf B})$ on the {\it ab}-component of the magnetic field at fixed {\it c} -component. Using Langevin dynamic simulations of two-dimensional vortex arrays we calculate density and phase correlation functions at different temperatures. Calculated phase correlations describe very well the experimental angular dependence of the plasma resonance field. We also demonstrate that in the case of weak damping in the liquid phase, broadening of the JPR line is caused mainly by random Josephson coupling arising from the density fluctuations of pancake vortices. In this case the JPR line has a universal shape, which is determined only by parameters of the superconductors and temperature.Comment: 22 pages, 6 figures, to appear in Phys. Rev. B, December

Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs

Prunella vulgaris: A comprehensive review of chemical constituents, pharmacological effects and clinical applications.

Prunella vulgaris (PV) is a perennial herb belonging to the Labiate family and is widely distributed in northeastern Asian countries such as Korea, Japan, and China. It is reported to display diverse biological activities including anti-microbial, anti-cancer, and anti-inflammation as determined by in vitro or in vivo studies. So far, about 200 compounds have been isolated from PV plant and majority of these have been characterized mainly as triterpenoids, sterols and flavonoids, followed by coumarins, phenylpropanoids, polysaccharides and volatile oils. This review summarizes and analyzes the current knowledge on the chemical constituents, pharmacological activities, mechanisms of action and clinical applications of the PV plant including its potential as a future medicinal plant. Although some of the chemical constituents of the PV plant and their mechanism of action have been investigated the biological activities of many of these remain unknown and further clinical trials are required to further enhance its reputation as a medicinal plant