Prospects for Spin-1 Resonance Search at 13 TeV LHC and the ATLAS Diboson Excess

Motivated by ATLAS diboson excess around 2 TeV, we investigate a phenomenology of spin-1 resonances in a model where electroweak sector in the SM is weakly coupled to strong dynamics. The spin-1 resonances, W' and Z', are introduced as effective degrees of freedom of the dynamical sector. We explore several theoretical constraints by investigating the scalar potential of the model as well as the current bounds from the LHC and precision measurements. It is found that the main decay modes are V' -> VV and V' -> Vh, and the V' width is narrow enough so that the ATLAS diboson excess can be explained. In order to investigate future prospects, we also perform collider simulations at the 13 TeV LHC, and obtain a model independent expected exclusion limit for the process pp -> W' -> WZ -> JJ. We find a parameter space where the diboson excess can be explained, and are within a reach of the LHC at the integrated luminosity of 10 fb-1 and 13 TeV.Comment: 38 pages, 19 figures, 1 table; minor changes, references added, version published in JHE

International consensus (ICON) on treatment of Ménière's disease

Objective: To present the international consensus for recommendations for Ménière's disease (MD) treatment. Methods: Based on a literature review and report of 4 experts from 4 continents, the recommendations have been presented during the 21st IFOS congress in Paris, in June 2017 and are presented in this work. Results: The recommendation is to change the lifestyle, to use the vestibular rehabilitation in the intercritic period and to propose psychotherapy. As a conservative medical treatment of first line, the authors recommend to use diuretics and Betahistine or local pressure therapy. When medical treatment fails, the recommendation is to use a second line treatment, which consists in the intratympanic injection of steroids. Then as a third line treatment, depending on the hearing function, could be either the endolymphatic sac surgery (when hearing is worth being preserved) or the intratympanic injection of gentamicin (with higher risks of hearing loss). The very last option is the destructive surgical treatment labyrinthectomy, associated or not to cochlear implantation or vestibular nerve section (when hearing is worth being preserved), which is the most frequent option

Comparison of electric dipole moments and the Large Hadron Collider for probing CP violation in triple boson vertices

CP violation from physics beyond the Standard Model may reside in triple boson vertices of the electroweak theory. We review the effective theory description and discuss how CP violating contributions to these vertices might be discerned by electric dipole moments (EDM) or diboson production at the Large Hadron Collider (LHC). Despite triple boson CP violating interactions entering EDMs only at the two-loop level, we find that EDM experiments are generally more powerful than the diboson processes. To give example to these general considerations we perform the comparison between EDMs and collider observables within supersymmetric theories that have heavy sfermions, such that substantive EDMs at the one-loop level are disallowed. EDMs generally remain more powerful probes, and next-generation EDM experiments may surpass even the most optimistic assumptions for LHC sensitivities.Comment: 26 pages, 14 figures, published version with more argument

Distribution-free stochastic model updating with staircase density functions

In stochastic model updating, hybrid uncertainties are typically characterized by the distributional p-box. It assigns a certain probability distribution to model parameters and assumes its hyper-parameters as interval values. Thus, regardless of the updating method employed, the distribution family needs to be known a priori to parameterize the distribution. Meanwhile, a novel class of the random variable, called staircase random variable, can discretely approximate a wide range of distributions by solving moment-matching optimization problem. The first author and his co-workers have recently developed a distribution-free stochastic updating framework, in which model parameters are considered as staircase random variables and their hyper-parameters are inferred in a Bayesian fashion. This framework can explore an optimal distribution from a broad range of potential distributions according to the available data. This study aims to further demonstrate the capability of this framework through a simple numerical example with a parameter following various types of distributions

Lamellae Stability in Confined Systems with Gravity

The microphase separation of a diblock copolymer melt confined by hard walls and in the presence of a gravitational field is simulated by means of a cell dynamical system model. It is found that the presence of hard walls normal to the gravitational field are key ingredients to the formation of well ordered lamellae in BCP melts. To this effect the currents in the directions normal and parallel to the field are calculated along the interface of a lamellar domain, showing that the formation of lamellae parallel to the hard boundaries and normal to the field correspond to the stable configuration. Also, it is found thet the field increases the interface width.Comment: 4 pages, 2 figures, submitted to Physical Review

Cardiac rupture after catheter ablation procedure

ArticleAnnals of Thoracic Surgery. 80(1): 326-328 (2005)journal articl

Crack Parameter Characterization by a Neural Network

A neural network with binary outputs is presented to determine the angle and the depth of a surface-breaking crack from ultrasonic backscattering data. The estimation procedure is divided into two steps: (1) The angle of the crack is estimated in the range from 10 to 70 degrees with a precision of 5 degrees. To improve the accuracy of estimation, information on the integral of the backscattered signal is utilized. (2) When the angle of the crack has been estimated, the depth of the crack is determined with a precision of 0.5mm in the range from 2.0mm to 4.0mm. This determination is achieved by employing sets of neural networks corresponding to various angles of the crack

Crack-depth determination by a neural network with a synthetic training data set

A neural network with an analog output is presented for crack-depth estimation from ultrasonic signals backscattered from a surface-breaking crack in a steel plate. The network has only one response unit and this unit directly reports the crack depth from the measured signals. A completely synthetic data set, spot-checked by comparison with experimental results, is utilized for the training of the network. The synthetic data set has been obtained by solving governing boundary integral equations by the boundary element method. A Gaussian modulated sinusoid has been utilized as incident signal. The architecture of the present network, which is a feedforward three-layered network together with an error back- propagation algorithm, has been discussed in Refs. [1,2]

Neural Network for Crack-Depth Determination from Ultrasonic Backscattering Dat

A neural network approach has been developed to determine the depth of a surface breaking crack in a steel plate from ultrasonic backscattering data. The network is trained by the use of a feedforward three-layered network together with a back-propagation algorithm for error corrections[1,2]. The signal used for crack insonification is a mode converted 45° transverse wave. The plate containing a surface breaking crack is immersed in water and the crack is insonified from the opposite uncracked side of the plate. A numerical analysis of the backscattered field is carried out based on elastic wave theory, by the use of the boundary element method. The numerical data are calibrated by comparison with experimental data. The computed backscattered field provides synthetic data for the training of the network. The training data have been calculated for cracks with specified increments of the crack depth. The performance of the network has been tested on experimental data for cracks of different depths than used for network training