SCR of NO with C3H6 in the presence of excess O2 over Cu/Ag/CeO2-ZrO2 catalyst

The catalytic activity of a series of CeO2-ZrO2 mixed oxides in the selective catalytic reduction (SCR) of NO by C3H6 at 400'C has been investigated. The NO reduction activity of pure CeO2 is enhanced in the presence of Zr, reaching a maximum NO conversion with CeO2(75)-ZrO2(25) catalyst. Then, the catalytic performances of Cu(4)/Ag(1)/CeO2 and Cu(4)/Ag(1)/CeO2(75)-ZrO2(25) catalysts were compared and the latter showed better activity especially in the low temperature region (250-350 C). The stronger metal-support interaction and higher reducibility shown by the Cu(4)/Ag(1)/CeO2(75)-ZrO2(25) catalyst were believed to enhance its performance compared to Cu(4)/Ag(1)/CeO2 catalyst by activating more C3H6 to selectively reduce NO within this temperature region. Central composite response surface design methodology was employed to study the effect of operating variables such as temperature, NO and C3H6 concentrations on the SCR of NO by C3H6 over Cu(4)/Ag(1)/CeO2(75)-ZrO2(25) catalyst and to determine the optimum value of operating variables for maximum NO conversion. Numerical results indicated that the optimum NO conversion of 82.89% is attained at reaction temperature =415.38 C, NO concentration= 1827.16 ppm and C3H6 concentration = 1908.13 ppm. The addition of water vapor to the reactant significantly decreased the NO conversion over Cu(4)/Ag(1)/CeO2 and Cu(4)/Ag(1)/CeO2 (75)-ZrO2(25), but the inhibition was more pronounced over Cu(4)/Ag(1)/CeO2 catalyst

Prototyping Incentive-based Resource Assignment for Clouds in Community Networks

Wireless community networks are a successful example of a collective where communities operate ICT infrastructure and provide IP connectivity based on the principle of reciprocal resource sharing of network bandwidth. This sharing, however, has not extended to computing and storage resources, resulting in very few applications and services which are currently deployed within community networks. Cloud computing, as in today's Internet, has made it common to consume resources provided by public clouds providers, but such cloud infrastructures have not materialized within community networks. We analyse in this paper socio-technical characteristics of community networks in order to derive scenarios for community clouds. Based on an architecture for such a community cloud, we implement a prototype for the incentive-driven resource assignment component, deploy it in a testbed of community network nodes, and evaluate its behaviour experimentally. Our evaluation gives insight into how the deployed prototype components regulate the consumption of cloud resources taking into account the users' contributions, and how this regulation affects the system usage. Our results suggest a further integration of this regulation component into current cloud management platforms in order to open them up for the operation of an ecosystem of community cloud

Support Service for Reciprocal Computational Resource Sharing in Wireless Community Networks

In community networks, individuals and local organizations from a geographic area team up to create and run a community-owned IP network to satisfy the community's demand for ICT, such as facilitating Internet access and providing services of local interest. Most current community networks use wireless links for the node interconnection, applying off-the-shelf wireless equipment. While IP connectivity over the shared network infrastructure is successfully achieved, the deployment of applications in community networks is surprisingly low. To address the solution of this problem, we propose in this paper a service to incentivize the contribution of computing and storage as cloud resources to community networks, in order to stimulate the deployment of services and applications. Our final goal is the vision that in the long term, the users of community networks will not need to consume applications from the Internet, but find them within the wireless community network

Non-Markovian incoherent quantum dynamics of a two-state system

We present a detailed study of the non-Markovian two-state system dynamics for the regime of incoherent quantum tunneling. Using perturbation theory in the system tunneling amplitude $\Delta$, and in the limit of strong system-bath coupling, we determine the short time evolution of the reduced density matrix and thereby find a general equation of motion for the non-Markovian evolution at longer times. We relate the nonlocality in time due to the non-Markovian effects with the environment characteristic response time. In addition, we study the incoherent evolution of a system with a double-well potential, where each well consists several quantized energy levels. We determine the crossover temperature to a regime where many energy levels in the wells participate in the tunneling process, and observe that the required temperature can be much smaller than the one associated with the system plasma frequency. We also discuss experimental implications of our theoretical analysis.Comment: 10 pages, published versio

Simultaneously Structured Models with Application to Sparse and Low-rank Matrices

The topic of recovery of a structured model given a small number of linear observations has been well-studied in recent years. Examples include recovering sparse or group-sparse vectors, low-rank matrices, and the sum of sparse and low-rank matrices, among others. In various applications in signal processing and machine learning, the model of interest is known to be structured in several ways at the same time, for example, a matrix that is simultaneously sparse and low-rank. Often norms that promote each individual structure are known, and allow for recovery using an order-wise optimal number of measurements (e.g., $\ell_1$ norm for sparsity, nuclear norm for matrix rank). Hence, it is reasonable to minimize a combination of such norms. We show that, surprisingly, if we use multi-objective optimization with these norms, then we can do no better, order-wise, than an algorithm that exploits only one of the present structures. This result suggests that to fully exploit the multiple structures, we need an entirely new convex relaxation, i.e. not one that is a function of the convex relaxations used for each structure. We then specialize our results to the case of sparse and low-rank matrices. We show that a nonconvex formulation of the problem can recover the model from very few measurements, which is on the order of the degrees of freedom of the matrix, whereas the convex problem obtained from a combination of the $\ell_1$ and nuclear norms requires many more measurements. This proves an order-wise gap between the performance of the convex and nonconvex recovery problems in this case. Our framework applies to arbitrary structure-inducing norms as well as to a wide range of measurement ensembles. This allows us to give performance bounds for problems such as sparse phase retrieval and low-rank tensor completion.Comment: 38 pages, 9 figure

Regulation of arginine transport by GCN2 eIF2 kinase is important for replication of the intracellular parasite Toxoplasma gondii

Toxoplasma gondii is a prevalent protozoan parasite that can infect any nucleated cell but cannot replicate outside of its host cell. Toxoplasma is auxotrophic for several nutrients including arginine, tryptophan, and purines, which it must acquire from its host cell. The demands of parasite replication rapidly deplete the host cell of these essential nutrients, yet Toxoplasma successfully manages to proliferate until it lyses the host cell. In eukaryotic cells, nutrient starvation can induce the integrated stress response (ISR) through phosphorylation of an essential translation factor eIF2. Phosphorylation of eIF2 lowers global protein synthesis coincident with preferential translation of gene transcripts involved in stress adaptation, such as that encoding the transcription factor ATF4 (CREB2), which activates genes that modulate amino acid metabolism and uptake. Here, we discovered that the ISR is induced in host cells infected with Toxoplasma. Our results show that as Toxoplasma depletes host cell arginine, the host cell phosphorylates eIF2 via protein kinase GCN2 (EIF2AK4), leading to induced ATF4. Increased ATF4 then enhances expression of the cationic amino acid transporter CAT1 (SLC7A1), resulting in increased uptake of arginine in Toxoplasma-infected cells. Deletion of host GCN2, or its downstream effectors ATF4 and CAT1, lowers arginine levels in the host, impairing proliferation of the parasite. Our findings establish that Toxoplasma usurps the host cell ISR to help secure nutrients that it needs for parasite replication

Development of optical data processing techniques applicable to detection and study of meteor trails

Development of coherent optical data processing techniques applicable to detection of meteor trails and examination of propertie

Distinguishing noise from chaos: objective versus subjective criteria using Horizontal Visibility Graph

A recently proposed methodology called the Horizontal Visibility Graph (HVG) [Luque {\it et al.}, Phys. Rev. E., 80, 046103 (2009)] that constitutes a geometrical simplification of the well known Visibility Graph algorithm [Lacasa {\it et al.\/}, Proc. Natl. Sci. U.S.A. 105, 4972 (2008)], has been used to study the distinction between deterministic and stochastic components in time series [L. Lacasa and R. Toral, Phys. Rev. E., 82, 036120 (2010)]. Specifically, the authors propose that the node degree distribution of these processes follows an exponential functional of the form $P(\kappa)\sim \exp(-\lambda~\kappa)$, in which $\kappa$ is the node degree and $\lambda$ is a positive parameter able to distinguish between deterministic (chaotic) and stochastic (uncorrelated and correlated) dynamics. In this work, we investigate the characteristics of the node degree distributions constructed by using HVG, for time series corresponding to $28$ chaotic maps and $3$ different stochastic processes. We thoroughly study the methodology proposed by Lacasa and Toral finding several cases for which their hypothesis is not valid. We propose a methodology that uses the HVG together with Information Theory quantifiers. An extensive and careful analysis of the node degree distributions obtained by applying HVG allow us to conclude that the Fisher-Shannon information plane is a remarkable tool able to graphically represent the different nature, deterministic or stochastic, of the systems under study.Comment: Submitted to PLOS On

Corotation Resonance and Diskoseismology Modes of Black Hole Accretion Disks

We demonstrate that the corotation resonance affects only some non-axisymmetric g-mode oscillations of thin accretion disks, since it is located within their capture zones. Using a more general (weaker radial WKB approximation) formulation of the governing equations, such g-modes, treated as perfect fluid perturbations, are shown to formally diverge at the position of the corotation resonance. A small amount of viscosity adds a small imaginary part to the eigenfrequency which has been shown to induce a secular instability (mode growth) if it acts hydrodynamically. The g-mode corotation resonance divergence disappears, but the mode magnitude can remain largest at the place of the corotation resonance. For the known g-modes with moderate values of the radial mode number and axial mode number (and any vertical mode number), the corotation resonance lies well outside their trapping region (and inside the innermost stable circular orbit), so the observationally relevant modes are unaffected by the resonance. The axisymmetric g-mode has been seen by Reynolds & Miller in a recent inviscid hydrodynamic accretion disk global numerical simulation. We also point out that the g-mode eigenfrequencies are approximately proportional to m for axial mode numbers |m|>0.Comment: 16 pages, no figures. Submitted to The Astrophysical Journa