Evidence of Wγγ production in pp collisions at s√=8 TeV and limits on anomalous quartic gauge couplings with the ATLAS detector

This Letter reports evidence of triple gauge boson production pp→W(ℓν)γγ+X, which is accessible for the first time with the 8 TeV LHC data set. The fiducial cross section for this process is measured in a data sample corresponding to an integrated luminosity of 20.3 fb−1, collected by the ATLAS detector in 2012. Events are selected using the W boson decay to eν or μν as well as requiring two isolated photons. The measured cross section is used to set limits on anomalous quartic gauge couplings in the high diphoton mass region.

Measurement of the WW+WZ cross section and limits on anomalous triple gauge couplings using final states with one lepton, missing transverse momentum, and two jets with the ATLAS detector at s√=7 TeV

The production of a W boson decaying to eν or μν in association with a W or Z boson decaying to two jets is studied using 4.6 fb−1 of proton--proton collision data at s√=7 TeV recorded with the ATLAS detector at the LHC. The combined WW+WZ cross section is measured with a significance of 3.4σ and is found to be 68±7 (stat.)±19 (syst.) pb, in agreement with the Standard Model expectation of 61.1±2.2 pb. The distribution of the transverse momentum of the dijet system is used to set limits on anomalous contributions to the triple gauge coupling vertices and on parameters of an effective-field-theory model.

Search for anomalous production of prompt same-sign lepton pairs and pair-produced doubly charged Higgs bosons with s√ = 8 TeV pp collisions using the ATLAS detector

A low-background inclusive search for new physics in events with same-sign dileptons is presented. The search uses proton--proton collisions corresponding to 20.3 fb−1 of integrated luminosity taken in 2012 at a centre-of-mass energy of 8 TeV with the ATLAS detector at the LHC. Pairs of isolated leptons with the same electric charge and large transverse momenta of the type e±e±,e±μ±, and μ±μ± are selected and their invariant mass distribution is examined. No excess of events above the expected level of Standard Model background is found. The results are used to set upper limits on the cross sections for processes beyond the Standard Model. Limits are placed as a function of the dilepton invariant mass within a fiducial region corresponding to the signal event selection criteria. Exclusion limits are also derived for a specific model of doubly charged Higgs boson production.

The display gamut available to simulate colors perceived by anomalous trichromats

The aim of this work was to investigate the effect on a display gamut of varying the optical density and the position of the maximum sensitivity of the cones spectra of anomalous trichromatic observers. The anomalous cone spectral sensitivities were estimated for a set of varying optical density and maximum sensitivity spectra conditions and used to compute the display color gamut. The computed display gamut simulated for normal observers the chro- matic diversity perceived by anomalous observers. It was found that even small variations on the optical density and on the position of the maximum sensitivity spectra have an impact on the simulations of the display gamut for anomalous observers. It was also found that simulations for deuteroanomalous observers are the ones with greater impact if the estimation of the corresponding color display gamut is not carefully adjusted for the observer.

Monitoring energy consumption in android applications

Dissertação de Mestrado em Engenharia Informática

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Influência de filtros de ruído dinâmico na perceção das cores utilizando um novo teste de visão das cores

Dissertação de mestrado em Optometria Avançada

Search for new phenomena in events with three or more charged leptons in pp collisions at TeV with the ATLAS detector

A generic search for anomalous production of events with at least three charged leptons is presented. The data sample consists of pp collisions at s√=8 TeV collected in 2012 by the ATLAS experiment at the CERN Large Hadron Collider, and corresponds to an integrated luminosity of 20.3 fb−1. Events are required to have at least three selected lepton candidates, at least two of which must be electrons or muons, while the third may be a hadronically decaying tau. Selected events are categorized based on their lepton flavour content and signal regions are constructed using several kinematic variables of interest. No significant deviations from Standard Model predictions are observed. Model-independent upper limits on contributions from beyond the Standard Model phenomena are provided for each signal region, along with prescription to re-interpret the limits for any model. Constraints are also placed on models predicting doubly charged Higgs bosons and excited leptons. For doubly charged Higgs bosons decaying to eτ or μτ, lower limits on the mass are set at 400 GeV at 95% confidence level. For excited leptons, constraints are provided as functions of both the mass of the excited state and the compositeness scale Λ, with the strongest mass constraints arising in regions where the mass equals Λ. In such scenarios, lower mass limits are set at 3.0 TeV for excited electrons and muons, 2.5 TeV for excited taus, and 1.6 TeV for every excited-neutrino flavour.

Development and characterization of lipid-based nanosystems for controlled release of bioactive compounds

Tese de Doutoramento em Engenharia Química e Biológica.