A New Achievable Scheme for Interference Relay Channels

We establish an achievable rate region for discrete memoryless interference relay channels that consist of two source-destination pairs and one or more relays. We develop an achievable scheme combining Han-Kobayashi and noisy network coding schemes. We apply our achievability to two cases. First, we characterize the capacity region of a class of discrete memoryless interference relay channels. This class naturally generalizes the injective deterministic discrete memoryless interference channel by El Gamal and Costa and the deterministic discrete memoryless relay channel with orthogonal receiver components by Kim. Moreover, for the Gaussian interference relay channel with orthogonal receiver components, we show that our scheme achieves a better sum rate than that of noisy network coding.Comment: 18 pages, 4 figure

Particulate counter electrode system for enhanced light harvesting in dye-sensitized solar cells

A particulate counter electrode with photo scattering and redox catalytic properties is applied to dye sensitized solar cells (DSSCs) in order to improve photo conversion efficiency and simplify the assembly process. Our particulate counter electrode acts as both a photo reflecting layer and a catalyst for reduction of electrolyte. The reflective and catalytic properties of the electrode are investigated through optical and electrochemical analysis, respectively. A short circuit current density enhancement is observed in the DSSCs without the need to add an additional reflecting layer to the electrode. This leads to a simplified assembly process. (C) 2013 Optical Society of Americ

Daylight-driven rechargeable antibacterial and antiviral nanofibrous membranes for bioprotective applications.

Emerging infectious diseases (EIDs) are a significant burden on global economies and public health. Most present personal protective equipment used to prevent EID transmission and infections is typically devoid of antimicrobial activity. We report on green bioprotective nanofibrous membranes (RNMs) with rechargeable antibacterial and antiviral activities that can effectively produce biocidal reactive oxygen species (ROS) solely driven by the daylight. The premise of the design is that the photoactive RNMs can store the biocidal activity under light irradiation and readily release ROS under dim light or dark conditions, making the biocidal function "always online." The resulting RNMs exhibit integrated properties of fast ROS production, ease of activity storing, long-term durability, robust breathability, interception of fine particles (>99%), and high bactericidal (>99.9999%) and virucidal (>99.999%) efficacy, which enabled to serve as a scalable biocidal layer for protective equipment by providing contact killing against pathogens either in aerosol or in liquid forms. The successful synthesis of these fascinating materials may provide new insights into the development of protection materials in a sustainable, self-recharging, and structurally adaptive form

An Efficient State Space Generation for the Analysis of Real-Time Systems

State explosion is a well-known problem that impedes analysis and testing based on state-space exploration. This problem is particularly serious in real-time systems because unbounded time values cause the state space to be infinite even for simple systems. In this paper, we present an algorithm that produces a compact representation of the reachable state space of a real-time system. The algorithm yields a small state space, but still retains enough information for analysis. To avoid the state explosion which can be caused by simply adding time values to states, our algorithm uses history equivalence and transition bisimulation to collapse states into equivalent classes. Through history equivalence, states are merged into an equivalence class with the same untimed executions up to the states. Using transition bisimulation, the states that have the same future behaviors are further collapsed. The resultant state space is finite and can be used to analyze real-time properties. To show the effectiveness of our algorithm, we have implemented the algorithm and have analyzed several example applications

Electrochemical sensing of angiogenin induced endothelial nitric oxide synthase activity

This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the Italian Union of Thermofluid dynamics, the Process Intensification Network, HEXAG - the Heat Exchange Action Group and the Institute of Mathematics and its Applications.Angiogenesis, formation of new blood vessels, is a complex but critical phenomenon. In particular, it is regulated by different angiogenic factors. Nitric oxide (NO) is also a very well known biological mediator involved in vascular physiology. This study focuses on relationships between the effect of angiogenin, a major angiogenic factor, and extracellular NO release. NO concentration was sensed electrochemically using a fibronectin coated multiple microelectrode array. Angiogenin was shown to increase NO levels, thus triggering nitric oxide synthase (NOS) activity. Angiogenin reactive pathway being very complex, we have used various selective inhibitors of angiogenin to investigate the mechanism leading to NO production. Neomycin, an antibiotic blocking nuclear translocation, inhibited angiogenin effect on NOS. This result demonstrates that angiogenin activates NOS by interacting with the cell nucleus.This study is funded by Medermica Ltd; the DIUS; KICOS (K20602000681-08B0100-02210); the Korea Science and Engineering Foundation (M10749000231-08N4900-23110); and the Korea Biotech R&D Group of Next-Generation Growth Engine Project (F104AB010004-08A0201-00410)

Two-dimensional hourglass Weyl nodal loop in monolayer Pb(ClO2_{2})2_{2} and Sr(ClO2_{2})2_{2}

The hourglass fermions in solid-state materials have been attracting significant interest recently. However, realistic two-dimensional (2D) materials with hourglass-shaped band structures are still very scarce. Here, through the first-principles calculations, we identify the monolayer Pb(ClO$_{2}$)$_{2}$ and Sr(ClO$_{2}$)$_{2}$ materials as the new realistic materials platform to realize 2D hourglass Weyl nodal loop. We show that these monolayer materials possess an hourglass Weyl nodal loop circling around the $\Gamma$ point and Weyl nodal line on the Brillouin zone (BZ) boundary in the absence of spin-orbit coupling (SOC). Through the symmetry analysis, we demonstrate that the hourglass Weyl nodal loop and Weyl nodal line are protected by the nonsymmorphic symmetries, and are robust under the biaxial strains. When we include the SOC, a tiny gap will be opened in the hourglass nodal loop and nodal line, and the nodal line can be transformed into the spin-orbit Dirac points. Our results provide a new realistic material platform for studying the intriguing physics associated with the 2D hourglass Weyl nodal loop and spin-orbit Dirac points.Comment: 10 pages, 7 figures, Accepted for publication in New Journal of Physic

Recursive nearest neighbor co‐kriging models for big multi‐fidelity spatial data sets

Big datasets are gathered daily from different remote sensing platforms. Recently, statistical co‐kriging models, with the help of scalable techniques, have been able to combine such datasets by using spatially varying bias corrections. The associated Bayesian inference for these models is usually facilitated via Markov chain Monte Carlo (MCMC) methods which present (sometimes prohibitively) slow mixing and convergence because they require the simulation of high‐dimensional random effect vectors from their posteriors given large datasets. To enable fast inference in big data spatial problems, we propose the recursive nearest neighbor co‐kriging (RNNC) model. Based on this model, we develop two computationally efficient inferential procedures: (a) the collapsed RNNC which reduces the posterior sampling space by integrating out the latent processes, and (b) the conjugate RNNC, an MCMC free inference which significantly reduces the computational time without sacrificing prediction accuracy. An important highlight of conjugate RNNC is that it enables fast inference in massive multifidelity data sets by avoiding expensive integration algorithms. The efficient computational and good predictive performances of our proposed algorithms are demonstrated on benchmark examples and the analysis of the High‐resolution Infrared Radiation Sounder data gathered from two NOAA polar orbiting satellites in which we managed to reduce the computational time from multiple hours to just a few minutes

Recursive Nearest Neighbor Co-Kriging Models for Big Multiple Fidelity Spatial Data Sets

Big datasets are gathered daily from different remote sensing platforms. Recently, statistical co-kriging models, with the help of scalable techniques, have been able to combine such datasets by using spatially varying bias corrections. The associated Bayesian inference for these models is usually facilitated via Markov chain Monte Carlo (MCMC) methods which present (sometimes prohibitively) slow mixing and convergence because they require the simulation of high-dimensional random effect vectors from their posteriors given large datasets. To enable fast inference in big data spatial problems, we propose the recursive nearest neighbor co-kriging (RNNC) model. Based on this model, we develop two computationally efficient inferential procedures: a) the collapsed RNNC which reduces the posterior sampling space by integrating out the latent processes, and b) the conjugate RNNC, an MCMC free inference which significantly reduces the computational time without sacrificing prediction accuracy. An important highlight of conjugate RNNC is that it enables fast inference in massive multifidelity data sets by avoiding expensive integration algorithms. The efficient computational and good predictive performances of our proposed algorithms are demonstrated on benchmark examples and the analysis of the High-resolution Infrared Radiation Sounder data gathered from two NOAA polar orbiting satellites in which we managed to reduce the computational time from multiple hours to just a few minutes.Comment: arXiv admin note: text overlap with arXiv:2004.0134