Air-coupled ultrasonic cure monitoring of composite matrices

none4Paper ID 1433, Session R15: NDT: Industrial appllicationsF. LIONETTO; A. TARZIA; M. COLUCCIA; A. MAFFEZZOLILionetto, Francesca; A., Tarzia; M., Coluccia; Maffezzoli, Alfons

Search for New Particles in Two-Jet Final States in 7 TeV Proton-Proton Collisions with the ATLAS Detector at the LHC

none15siA search for new heavy particles manifested as resonances in two-jet final states is presented. The data were produced in 7 TeV proton-proton collisions by the LHC and correspond to an integrated luminosity of 315 nb␣1 collected by the ATLAS detector. No resonances were observed. Upper limits were set on the product of cross section and signal acceptance for excited-quark (q0) production as a function of q0 mass. These exclude at the 95% C.L. the q0 mass interval 0:30 < mq0 < 1:26 TeV, extending the reach of previous experiments.G. Aad; M. Bianco; E. Brambilla; G. Cataldi; A. Cazzato; G. Chiodini; R. Coluccia; R. Crupi; E. Gorini; F. Grancagnolo; A. Guida; R. Perrino; M. Primavera; S. Spagnolo; A. Ventura; et al.G., Aad; Bianco, Michele; Brambilla, Elena; G., Cataldi; A., Cazzato; G., Chiodini; Coluccia, MARIA RITA; Crupi, Roberto; Gorini, Edoardo; F., Grancagnolo; Guida, Angelo; R., Perrino; Primavera, Margherita; Spagnolo, Stefania Antonia; Ventura, Andre

An application of the option-pricing model to the valuation of football player in the ‘Serie A League’

Football is perhaps the most popular sport in the world. The market of football players is one of the most popular factors of the sport that makes the fans dream of each team which increases the interest around the sport. In 2013 the player Gareth Bale was sold from Tottenham to Real Madrid for 100 million Euros. Someone argues that the market for football players is inherently irrational precisely because of the sale price of certain players. This paper is based on Tunaru et al. model that is real option based model. The aim of the paper is the financial valuation of a goalkeeper of Serie A League club. The model depends on relationship of player’s and team’s performance and the club’s turnover

Indolylarylsulfones, a fascinating story of highly potent human immunodeficiency virus type 1 non-nucleoside reverse transcriptase inhibitors

Indolylarylsulfones are a potent class of human immunodeficiency virus type 1 non-nucleoside reverse transcriptase inhibitors. In this review, the structure activity relationship (SAR) studies to improve the profile of sulfone L-737,126 discovered by Merck AG have been analysed with focus on introduction of the 3',5'-dimethyl groups at the 3-phenylsulfonyl moiety, the 2-hydroxyethyl tail at the indole-2-carboxamide nitrogen, coupling of the carboxamide nitrogen with one or two glycinamide and alaninamide units, a fluorine atom at position 4 of the indole ring and correlation between configuration of the asymmetric centre and linker length. IAS derivatives look like promising drug candidates for the treatment of AIDS and related infections in combination with other antiretroviral agents

Drug design and synthesis of first in class PDZ1 targeting NHERF1 inhibitors as anticancer agents

Targeted approaches aiming at modulating NHERF1 activity, rather than its overall expression, would be preferred to preserve the normal functions of this versatile protein. We focused our attention on the NHERF1/PDZ1 domain that governs its membrane recruitment/displacement through a transient phosphorylation switch. We herein report the design and synthesis of novel NHERF1 PDZ1 domain inhibitors. These compounds have potential therapeutic value when used in combination with antagonists of β-catenin to augment apoptotic death of colorectal cancer cells refractory to currently available Wnt/β-catenin-targeted agents

Differences in spatial memory recognition due to cognitive style

Field independence refers to the ability to perceive details from the surrounding context as a whole and to represent the environment by relying on an internal reference frame. Conversely, field dependence individuals tend to focus their attention on single environmental features analysing them individually. This cognitive style affects several visuo-spatial abilities including spatial memory. This study assesses both the effect of field independence and field dependence on performance displayed on virtual environments of different complexity. Forty young healthy individuals took part in this study. Participants performed the Embedded Figures Test for field independence or dependence assessment and a new spatial memory recognition test. The spatial memory recognition test demanded to memorize a green box location in a virtual room picture. Thereafter, during ten trials participants had to decide if a green box was located in the same position as in the sample picture. Five of the pictures were correct. The information available in the virtual room was manipulated. Hence, two different experimental conditions were tested: a virtual room containing all landmarks and a virtual room with only two cues. Accuracy and reaction time were registered. Analyses demonstrated that higher field independent individuals were related to better spatial memory performance in two landmarks condition and were faster in all landmark condition. In addition, men and women did not differ in their performance. These results suggested that cognitive style affects spatial memory performance and this phenomenon is modulated by environment complexity. This does not affect accuracy but time spent. Moreover, field dependent individuals are unable to organize the navigational field by relying on internal reference frames when few landmarks are available, and this causes them to commit more errors

Operational Rate-Distortion Performance of Single-source and Distributed Compressed Sensing

We consider correlated and distributed sources without cooperation at the encoder. For these sources, we derive the best achievable performance in the rate-distortion sense of any distributed compressed sensing scheme, under the constraint of high--rate quantization. Moreover, under this model we derive a closed--form expression of the rate gain achieved by taking into account the correlation of the sources at the receiver and a closed--form expression of the average performance of the oracle receiver for independent and joint reconstruction. Finally, we show experimentally that the exploitation of the correlation between the sources performs close to optimal and that the only penalty is due to the missing knowledge of the sparsity support as in (non distributed) compressed sensing. Even if the derivation is performed in the large system regime, where signal and system parameters tend to infinity, numerical results show that the equations match simulations for parameter values of practical interest.Comment: To appear in IEEE Transactions on Communication

Distributed Learning from Interactions in Social Networks

We consider a network scenario in which agents can evaluate each other according to a score graph that models some interactions. The goal is to design a distributed protocol, run by the agents, that allows them to learn their unknown state among a finite set of possible values. We propose a Bayesian framework in which scores and states are associated to probabilistic events with unknown parameters and hyperparameters, respectively. We show that each agent can learn its state by means of a local Bayesian classifier and a (centralized) Maximum-Likelihood (ML) estimator of parameter-hyperparameter that combines plain ML and Empirical Bayes approaches. By using tools from graphical models, which allow us to gain insight on conditional dependencies of scores and states, we provide a relaxed probabilistic model that ultimately leads to a parameter-hyperparameter estimator amenable to distributed computation. To highlight the appropriateness of the proposed relaxation, we demonstrate the distributed estimators on a social interaction set-up for user profiling.Comment: This submission is a shorter work (for conference publication) of a more comprehensive paper, already submitted as arXiv:1706.04081 (under review for journal publication). In this short submission only one social set-up is considered and only one of the relaxed estimators is proposed. Moreover, the exhaustive analysis, carried out in the longer manuscript, is completely missing in this versio

An Empirical Bayes Approach for Distributed Estimation of Spatial Fields

In this paper we consider a network of spatially distributed sensors which collect measurement samples of a spatial field, and aim at estimating in a distributed way (without any central coordinator) the entire field by suitably fusing all network data. We propose a general probabilistic model that can handle both partial knowledge of the physics generating the spatial field as well as a purely data-driven inference. Specifically, we adopt an Empirical Bayes approach in which the spatial field is modeled as a Gaussian Process, whose mean function is described by means of parametrized equations. We characterize the Empirical Bayes estimator when nodes are heterogeneous, i.e., perform a different number of measurements. Moreover, by exploiting the sparsity of both the covariance and the (parametrized) mean function of the Gaussian Process, we are able to design a distributed spatial field estimator. We corroborate the theoretical results with two numerical simulations: a stationary temperature field estimation in which the field is described by a partial differential (heat) equation, and a data driven inference in which the mean is parametrized by a cubic spline