Production of vector resonances at the LHC via WZ-scattering: a unitarized EChL analysis

In the present work we study the production of vector resonances at the LHC by means of the vector boson scattering $WZ \to WZ$ and explore the sensitivities to these resonances for the expected future LHC luminosities. We are assuming that these vector resonances are generated dynamically from the self interactions of the longitudinal gauge bosons, $W_L$ and $Z_L$, and work under the framework of the electroweak chiral Lagrangian to describe in a model independent way the supposedly strong dynamics of these modes. The properties of the vector resonances, mass, width and couplings to the $W$ and $Z$ gauge bosons are derived from the inverse amplitude method approach. We implement all these features into a single model, the IAM-MC, adapted for MonteCarlo, built in a Lagrangian language in terms of the electroweak chiral Lagrangian and a chiral Lagrangian for the vector resonances, which mimics the resonant behavior of the IAM and provides unitary amplitudes. The model has been implemented in MadGraph, allowing us to perform a realistic study of the signal versus background events at the LHC. In particular, we have focused our study on the $pp\to WZjj$ type of events, discussing first on the potential of the hadronic and semileptonic channels of the final $WZ$, and next exploring in more detail the clearest signals. These are provided by the leptonic decays of the gauge bosons, leading to a final state with $\ell_1^+\ell_1^-\ell_2^+\nu jj$, $\ell=e,\mu$, having a very distinctive signature, and showing clearly the emergence of the resonances with masses in the range of 1.5-2.5 TeV, which we have explored.Comment: Revised version accepted for publication in JHEP. Enlarged analysis. References added. 44 pages, 23 figures, 3 table

Quantum Estimation Methods for Quantum Illumination

Quantum illumination consists in shining quantum light on a target region immersed in a bright thermal bath, with the aim of detecting the presence of a possible low-reflective object. If the signal is entangled with the receiver, then a suitable choice of the measurement offers a gain with respect to the optimal classical protocol employing coherent states. Here, we tackle this detection problem by using quantum estimation techniques to measure the reflectivity parameter of the object, showing an enhancement in the signal-to-noise ratio up to 3 dB with respect to the classical case when implementing only local measurements. Our approach employs the quantum Fisher information to provide an upper bound for the error probability, supplies the concrete estimator saturating the bound, and extends the quantum illumination protocol to non-Gaussian states. As an example, we show how Schrodinger's cat states may be used for quantum illumination.Comment: Published versio

Refining the scalar and tensor contributions in τ→πππντ\tau\to \pi\pi\pi\nu_\tau decays

In this article we analyze the contribution from intermediate spin-0 and spin-2 resonances to the $\tau\to\nu \pi\pi\pi$ decay by means of a chiral invariant Lagrangian incorporating these mesons. In particular, we study the corresponding axial-vector form-factors. The advantage of this procedure with respect to previous analyses is that it incorporates chiral (and isospin) invariance and, hence, the partial conservation of the axial-vector current. This ensures the recovery of the right low-energy limit, described by chiral perturbation theory, and the transversality of the current in the chiral limit at all energies. Furthermore, the meson form-factors are further improved by requiring appropriate QCD high-energy conditions. We end up with a brief discussion on its implementation in the Tauola Monte Carlo and the prospects for future analyses of Belle's data.Comment: 32 pages, 13 figures. Extended discussion on the numerical importance of the tensor and scalar resonances and the parametrization of the scalar propagator. Version published in JHE

DMPSA appliCation reduces N2O emissions from exogenous NH4 + and NO3 - sources in irrigated maize

Agriculture is a major anthropogenic source of nitrous oxide (N2O). Application of nitrogenous (N) fertilizers enhances the emission of this greenhouse gas (GHG), mainly due to the biogenic processes of nitrification and denitrification. The use of nitrification inhibitors (NIs), that delay the microbial oxidation of NH4 + to NO3 -, has been reported as a successful tool for mitigating N2O losses. In this context, a field experiment using 15N labeled fertilizers was carried out in an irrigated Mediterranean maize field aiming to evaluate the effectiveness of the NI 2-(3,4-dimethyl-1H-pyrazol-1-yl) succinic acid isomeric mixture (DMPSA) on mitigating N2O emissions, and assess the processes involved in its production. The experiment, performed in 1 m2 microplots, involved the application of 15NH4NO3 or NH4 15NO3 - (with and without DMPSA) to quantify the amount of N2O coming from exogenous NH4 +, exogenous NO3 - and endogenous soil N. The resulting N2O fluxes confirmed that the addition of DMPSA led to a significant (54%) abatement of this GHG. In this experiment, both nitrification and denitrification were partially inhibited by DMPSA. When NI was not applied, the largest N2O emissions were expected from NH4 + than from NO3 --based fertilizers due to nitrification

Modelling the balance of care:Impact of an evidence-informed policy on a mental health ecosystem

Major efforts worldwide have been made to provide balanced Mental Health (MH) care. Any integrated MH ecosystem includes hospital and community-based care, highlighting the role of outpatient care in reducing relapses and readmissions. This study aimed (i) to identify potential expert-based causal relationships between inpatient and outpatient care variables, (ii) to assess them by using statistical procedures, and finally (iii) to assess the potential impact of a specific policy enhancing the MH care balance on real ecosystem performance. Causal relationships (Bayesian network) between inpatient and outpatient care variables were defined by expert knowledge and confirmed by using multivariate linear regression (generalized least squares). Based on the Bayesian network and regression results, a decision support system that combines data envelopment analysis, Monte Carlo simulation and fuzzy inference was used to assess the potential impact of the designed policy. As expected, there were strong statistical relationships between outpatient and inpatient care variables, which preliminarily confirmed their potential and a priori causal nature. The global impact of the proposed policy on the ecosystem was positive in terms of efficiency assessment, stability and entropy. To the best of our knowledge, this is the first study that formalized expert-based causal relationships between inpatient and outpatient care variables. These relationships, structured by a Bayesian network, can be used for designing evidence-informed policies trying to balance MH care provision. By integrating causal models and statistical analysis, decision support systems are useful tools to support evidence-informed planning and decision making, as they allow us to predict the potential impact of specific policies on the ecosystem prior to its real application, reducing the risk and considering the population’s needs and scientific findings

Biomarker comparison and selection for prostate cancer detection in Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI)

[EN] In this work, the capability of imaging biomarkers obtained from multivariate curve resolution-alternating least squares (MCR-ALS), in combination with those obtained from first and second-generation pharmacokinetic models, have been studied for improving prostate cancer tumor depiction using partial least squares- discriminant analysis (PLS-DA). The main goal of this work is to improve tissue classification properties selecting the best biomarkers in terms of prediction. A wrapped double cross-validation method has been applied for the variable selection process. Using the best PLS-DA model, prostate tissues can be classified obtaining 13.4% of false negatives and 7.4% of false positives. Using MCR-ALS biomarkers yields the best models in terms of parsimony and classification performance.This research has been supported by "Generalitat Valenciana (Conselleria d'Educacio, Investigacio, Cultura I Esport)" under the project AICO/2016/061.Aguado-Sarrió, E.; Prats-Montalbán, JM.; Sanz-Requena, R.; Garcia-Marti, G.; Marti-Bonmati, L.; Ferrer, A. (2017). Biomarker comparison and selection for prostate cancer detection in Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI). Chemometrics and Intelligent Laboratory Systems. 165:38-45. https://doi.org/10.1016/j.chemolab.2017.04.003S384516

Reactive belite stabilization mechanisms by boron-bearing dopants

Belite-rich cements hold promise for reduced energy consumption and CO2 emissions, but their use is hindered by the slow hydration rates of ordinary belites. This drawback may be overcome by activation of belite by doping. Here, the doping mechanism of B and Na/B in belites is reported. For B-doping, three solid solutions have been tested: Ca2-x/2□x/2(SiO4)1-x(BO3)x, Ca2(SiO4)1-x(BO3)xOx/2 and Ca2-xBx(SiO4)1-x(BO4)x. The experimental results support the substitution of silicate groups by tetrahedral borate groups with the concomitant substitution of calcium by boron for charge compensation, Ca2-xBx(SiO4)1-x(BO4)x. Otherwise, the coupled Na/B-doping of belite has also been investigated and Ca2-xNax(SiO4)1-x(BO3)x series is confirmed to exist for a large range of x values. Along this series, α'H-C2S is the main phase (for x≥0.10) and is single phase for x=0.25. Finally, a new structural description for borax doping in belite has been developed for α'H-Ca1.85Na0.15(SiO4)0.85(BO3)0.15, which fits better borax activated belite cements in Rietveld mineralogical analysisThis work has been supported by Spanish Ministry of Science and Innovation through MAT2010-16213 research grant which is cofunded by FEDER

Mechanism of stabilization of dicalcium silicate solid solution with aluminium

Stoichiometric dicalcium silicate, Ca2SiO4, displays a well-known polymorphism with temperature. When this phase is doped by a range of elements, belite, one of the main phases of cements, is generated. Here, we thoroughly study the aluminum doping of dicalcium silicate. This type of study is important for cement characterization and also from a basic point of view. Ca2Si1−2xAl2xO4−x□x (x = 0, 0.010, 0.014, 0.03) has been prepared and studied by X-ray powder diffraction and the Rietveld method. The limiting composition has been established as Ca2Si0.972Al0.028O3.986□0.014. The 27Al MAS NMR band located close to ∼−70 ppm is ascribed to tetrahedral environments, in agreement with the proposed aliovalent Si/Al atomic substitution mechanism. Thermal analysis measurements under a wet atmosphere indirectly confirm the increase of oxygen vacancies as the amount of incorporated protons increases with the aluminium content. A thorough electrical characterization has been carried out including overall conductivity measurements under wet and dry atmospheres and conductivity as a function of the oxygen partial pressure. The samples show oxide anion conductivity with a small p-type electronic contribution under oxidizing conditions. These compounds display a very important proton contribution to the overall conductivities under humidified atmospheres.This work has been supported by the Spanish Ministry of Science and Innovation through the research grant MAT2010- 15175 which is co-founded by FEDER and Junta de Andalucía (Spain) through the research grant P10-FQM-6680