Window Function for Non-Circular Beam CMB Anisotropy Experiment

We develop computationally rapid methods to compute the window function for a cosmic microwave background anisotropy experiment with a non-circular beam which scans over large angles on the sky. To concretely illustrate these methods we compute the window function for the Python V experiment which scans over large angles on the sky with an elliptical Gaussian beam.Comment: 27 pages, 5 figure

"ધ્યાન કરતા અને ધ્યાન ન કરતા સ્ત્રી-પુરુષોમાં સ્વ-નિયંત્રણ, મનોવૈજ્ઞાનિક સુખાકારી અને માનસિક સ્વાસ્થ્યનો તુલનાત્મક અભ્યાસ"

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Local Ranking Problem on the BrowseGraph

The "Local Ranking Problem" (LRP) is related to the computation of a centrality-like rank on a local graph, where the scores of the nodes could significantly differ from the ones computed on the global graph. Previous work has studied LRP on the hyperlink graph but never on the BrowseGraph, namely a graph where nodes are webpages and edges are browsing transitions. Recently, this graph has received more and more attention in many different tasks such as ranking, prediction and recommendation. However, a web-server has only the browsing traffic performed on its pages (local BrowseGraph) and, as a consequence, the local computation can lead to estimation errors, which hinders the increasing number of applications in the state of the art. Also, although the divergence between the local and global ranks has been measured, the possibility of estimating such divergence using only local knowledge has been mainly overlooked. These aspects are of great interest for online service providers who want to: (i) gauge their ability to correctly assess the importance of their resources only based on their local knowledge, and (ii) take into account real user browsing fluxes that better capture the actual user interest than the static hyperlink network. We study the LRP problem on a BrowseGraph from a large news provider, considering as subgraphs the aggregations of browsing traces of users coming from different domains. We show that the distance between rankings can be accurately predicted based only on structural information of the local graph, being able to achieve an average rank correlation as high as 0.8

Chemistry by Mobile Phone (or how to justify more time at the bar)

By combining automatic environment monitoring with Java smartphones a system has been produced for the real-time monitoring of experiments whilst away from the lab. Changes in the laboratory environment are encapsulated as simple XML messages, which are published using an MQTT compliant broker. Clients subscribe to the MQTT stream, and produce a user display. An MQTT client written for the Java MIDP platform, can be run on a smartphone with a GPRS Internet connection, freeing us from the constraints of the lab. We present an overview of the technologies used, and how these are helping chemists make the best use of their time

COBE-DMR-Normalized Dark Energy Cosmogony

Likelihood analyses of the COBE-DMR sky maps are used to determine the normalization of the inverse-power-law-potential scalar field dark energy model. Predictions of the DMR-normalized model are compared to various observations to constrain the allowed range of model parameters. Although the derived constraints are restrictive, evolving dark energy density scalar field models remain an observationally-viable alternative to the constant cosmological constant model.Comment: 26 pages, 10 figures, ApJ accepte

Numerical, analytical, experimental study of fluid dynamic forces in seals

NASA/Lewis Research Center is sponsoring a program for providing computer codes for analyzing and designing turbomachinery seals for future aerospace and engine systems. The program is made up of three principal components: (1) the development of advanced three dimensional (3-D) computational fluid dynamics codes, (2) the production of simpler two dimensional (2-D) industrial codes, and (3) the development of a knowledge based system (KBS) that contains an expert system to assist in seal selection and design. The first task has been to concentrate on cylindrical geometries with straight, tapered, and stepped bores. Improvements have been made by adoption of a colocated grid formulation, incorporation of higher order, time accurate schemes for transient analysis and high order discretization schemes for spatial derivatives. This report describes the mathematical formulations and presents a variety of 2-D results, including labyrinth and brush seal flows. Extensions of 3-D are presently in progress

Modeling mechanical properties of low carbon hot rolled steels

Steel is the most important material and it has several applications, and positions second to cement in its consumption in the world. The mechanical properties of steels are very important and vary significantly due to heat treatment, mechanical treatment, processing and alloying elements. The relationships between these parameters are complex, and nonlinear in nature. An artificial neural networks (ANN) model has been used for the prediction of mechanical properties of low alloy steels. The input parameters of the model consist of alloy composition (Al, Al soluble, C, Cr, Cu, Mn, Mo, Nb, Ni, P, S, Si, Ti, V and Nitrogen in ppm) and process parameters (coil target temperature, finish rolling temperature) and the outputs are ultimate tensile strength, yield strength, and percentage elongation. The model can be used to calculate properties of low alloy steels as a function of alloy composition and process parameters at new instances. The influence of inputs on properties of steels is simulated using the model. The results are in agreement with existing experimental knowledge. The developed model can be used as a guide for further alloy developmen

Non-Gaussian Error Distribution of Hubble Constant Measurements

We construct the error distribution of Hubble constant ($H_0$) measurements from Huchra's compilation of 461 measurements of $H_0$ and the WMAP experiment central value $H_0$ = 71 km s$^{-1}$ Mpc$^{-1}$. This error distribution is non-Gaussian, with significantly larger probability in the tails of the distribution than predicted by a Gaussian distribution. The 95.4 % confidence limits are 7.0 $\sigma$ in terms of the quoted errors. It is remarkably well described by either a widened $n = 2$ Student's $t$ distribution or a widened double exponential distribution. These conclusions are unchanged if we use instead the central value $H_0$ = 67 km s$^{-1}$ Mpc$^{-1}$ found from a median statistics analysis of a major subset of $H_0$ measurements used here.Comment: 12 pages, 8 figure

In-vitro susceptibility of multiple drug resistant Pseudomonas aeruginosa to organic acids

Objectives: Pseudomonas aeruginosa is a classic opportunistic pathogen with innate resistance to many antibiotics anddisinfectants. Resistance to antimicrobial agents makes it the most noxious organism to eliminate from infection site. Inview of its antimicrobial resistance, an attempt was made to study its susceptibility to various organic acids.Methods: Seven clinical isolates of P. aeruginosa resistant to multiple antibiotics were subjected to in vitro susceptibilityto various organic acids by broth dilution method to find out susceptibility to various organic acids.Results: The isolates of P. aeruginosa resistant to 14 antimicrobials were found susceptible to one percent oxalic acidand trichloroacetic acid, two percent lactic acid and citric acid, and three percent acetic acid. It is interesting to note thatstrains resistant to multiple antibiotics were also found susceptible to organic acids. Oxalic acid and trichloroacetic acidwere found highly effective.Conclusions: Clinical use of oxalic acid, trichloroacetic acid and lactic acid as topical agents to treat superficial pseudomonalinfections caused by difficult strains of P. aeruginosa may be recommended after confirmation of their toxicityand in vivo efficacy in animal models. J Microbiol Infect Dis 2013; 3(2): 67-70Key words: Pseudomonas aeruginosa, Multiple Antibiotic Resistance, Susceptibility to Organic Acid