Interactivity: a factor to increase memorization

Today, approximately 29% of the world population use the Internet, against 38% in Brazil, which shows its importance in people's routine not only in Brazil, but also worldwide. Being the Internet a communication media, this research evaluates the influence of Interactivity as a factor to increase memorization of Internet sites. According to literature, multiway, immediacy and contingency factors increase Interactivity and sites that provide one or more of these factors influence memorization. 20 in-depth personal interviews were conducted to improve the understanding the issue, to identify leads and elaborate our hypothesis, followed by a quantitative survey of 300 people. Hypotheses were tested using Chi-square and a hierarchical and non-hierarchical cluster analysis. Results showed that the smaller the number of leads of a specific website, the larger are its memorization and access. The theoretical contribution of this investigation is that websites that offer fewer leads are more interactive, which causes them to be remembered. The managerial implication is that websites with a clear position and a small quantity of information or leads tend to be more remembered and accessed by internet users.

Microbial Translocation Is Associated with Extensive Immune Activation in Dengue Virus Infected Patients with Severe Disease

Background: Severe dengue virus (DENV) disease is associated with extensive immune activation, characterized by a cytokine storm. Previously, elevated lipopolysaccharide (LPS) levels in dengue were found to correlate with clinical disease severity. In the present cross-sectional study we identified markers of microbial translocation and immune activation, which are associated with severe manifestations of DENV infection. Methods: Serum samples from DENV-infected patients were collected during the outbreak in 2010 in the State of Sa˜o Paulo, Brazil. Levels of LPS, lipopolysaccharide binding protein (LBP), soluble CD14 (sCD14) and IgM and IgG endotoxin core antibodies were determined by ELISA. Thirty cytokines were quantified using a multiplex luminex system. Patients were classified according to the 2009 WHO classification and the occurrence of plasma leakage/shock and hemorrhage. Moreover, a (non-supervised) cluster analysis based on the expression of the quantified cytokines was applied to identify groups of patients with similar cytokine profiles. Markers of microbial translocation were linked to groups with similar clinical disease severity and clusters with similar cytokine profiles. Results: Cluster analysis indicated that LPS levels were significantly increased in patients with a profound pro-inflammatory cytokine profile. LBP and sCD14 showed significantly increased levels in patients with severe disease in the clinical classification and in patients with severe inflammation in the cluster analysis. With both the clinical classification and the cluster analysis, levels of IL-6, IL-8, sIL-2R, MCP-1, RANTES, HGF, G-CSF and EGF were associated with severe disease. Conclusions: The present study provides evidence that both microbial translocation and extensive immune activation occur during severe DENV infection and may play an important role in the pathogenesis.

MHD numerical simulations of colliding winds in massive binary systems - I. Thermal versus non-thermal radio emission

In the past few decades detailed observations of radio and X-ray emission from massive binary systems revealed a whole new physics present in such systems. Both thermal and non-thermal components of this emission indicate that most of the radiation at these bands originates in shocks. O and B-type stars and WolfRayet (WR) stars present supersonic and massive winds that, when colliding, emit largely due to the freefree radiation. The non-thermal radio and X-ray emissions are due to synchrotron and inverse Compton processes, respectively. In this case, magnetic fields are expected to play an important role in the emission distribution. In the past few years the modelling of the freefree and synchrotron emissions from massive binary systems have been based on purely hydrodynamical simulations, and ad hoc assumptions regarding the distribution of magnetic energy and the field geometry. In this work we provide the first full magnetohydrodynamic numerical simulations of windwind collision in massive binary systems. We study the freefree emission characterizing its dependence on the stellar and orbital parameters. We also study self-consistently the evolution of the magnetic field at the shock region, obtaining also the synchrotron energy distribution integrated along different lines of sight. We show that the magnetic field in the shocks is larger than that obtained when the proportionality between B and the plasma density is assumed. Also, we show that the role of the synchrotron emission relative to the total radio emission has been underestimated.

Bayesian analysis of weak gravitational lensing and Sunyaev-Zel'dovich data for six galaxy clusters

We present an analysis of observations made with the Arcminute Microkelvin Imager (AMI) and the CanadaFranceHawaii Telescope (CFHT) of six galaxy clusters in a redshift range of 0.160.41. The cluster gas is modelled using the SunyaevZeldovich (SZ) data provided by AMI, while the total mass is modelled using the lensing data from the CFHT. In this paper, we (i) find very good agreement between SZ measurements (assuming large-scale virialization and a gas-fraction prior) and lensing measurements of the total cluster masses out to r200; (ii) perform the first multiple-component weak-lensing analysis of A115; (iii) confirm the unusual separation between the gas and mass components in A1914 and (iv) jointly analyse the SZ and lensing data for the relaxed cluster A611, confirming our use of a simulation-derived masstemperature relation for parametrizing measurements of the SZ effect.

The young stellar cluster [DBS2003] 157 associated with the H ii region GAL 331.31-00.34

We report a study of the stellar content of the near-infrared (NIR) cluster [DBS2003] 157 embedded in the extended H ii region GAL 331.31-00.34, which is associated with the IRAS source 16085-5138. JHK photometry was carried out in order to identify potential ionizing candidates, and the follow-up NIR spectroscopy allowed the spectral classification of some sources, including two O-type stars. A combination of NIR photometry and spectroscopy data was used to obtain the distance of these two stars, with the method of spectroscopic parallax: IRS 298 (O6 V, 3.35 +/- 0.61 kpc) and IRS 339 (O9 V, 3.24 +/- 0.56 kpc). Adopting the average distance of 3.29 +/- 0.58 kpc and comparing the Lyman continuum luminosity of these stars with that required to account for the radio continuum flux of the H ii region, we conclude that these two stars are the ionizing sources of GAL 331.31-00.34. Young stellar objects (YSOs) were searched by using our NIR photometry and mid-infrared (MIR) data from the Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE) survey. The analysis of NIR and MIR colourcolour diagrams resulted in 47 YSO candidates. The GLIMPSE counterpart of IRAS 16085-5138, which presents IRAS colour indices compatible with an ultracompact H ii region, has been identified. The analysis of its spectral energy distribution between 2 and m revealed that this source shows a spectral index a= 3.6 between 2 and m, which is typical of a YSO immersed in a protostellar envelope. Lower limits to the bolometric luminosity and the mass of the embedded protostar have been estimated as L= 7.7 x 10(3) L? and M= 10 M?, respectively, which correspond to a B0B1 V zero-age main sequence star.

FINDING FOSSIL GROUPS: OPTICAL IDENTIFICATION AND X-RAY CONFIRMATION

We report the discovery of 12 new fossil groups (FGs) of galaxies, systems dominated by a single giant elliptical galaxy and cluster-scale gravitational potential, but lacking the population of bright galaxies typically seen in galaxy clusters. These FGs, selected from the maxBCG optical cluster catalog, were detected in snapshot observations with the Chandra X-ray Observatory. We detail the highly successful selection method, with an 80% success rate in identifying 12 FGs from our target sample of 15 candidates. For 11 of the systems, we determine the X-ray luminosity, temperature, and hydrostatic mass, which do not deviate significantly from expectations for normal systems, spanning a range typical of rich groups and poor clusters of galaxies. A small number of detected FGs are morphologically irregular, possibly due to past mergers, interaction of the intra-group medium with a central active galactic nucleus (AGN), or superposition of multiple massive halos. Two-thirds of the X-ray-detected FGs exhibit X-ray emission associated with the central brightest cluster galaxy (BCG), although we are unable to distinguish between AGN and extended thermal galaxy emission using the current data. This sample representing a large increase in the number of known FGs, will be invaluable for future planned observations to determine FG temperature, gas density, metal abundance, and mass distributions, and to compare to normal (non-fossil) systems. Finally, the presence of a population of galaxy-poor systems may bias mass function determinations that measure richness from galaxy counts. When used to constrain power spectrum normalization and Omega(m), these biased mass functions may in turn bias these results.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.