Measurement of χ c1 and χ c2 production with √s = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at √s = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measure

Search for dark matter candidates and large extra dimensions in events with a jet and missing transverse momentum with the ATLAS detector

A search for new phenomena in events with a high-energy jet and large missing transverse momentum is performed using data from proton-proton collisions at s√=7TeV with the ATLAS experiment at the Large Hadron Collider. Four kinematic regions are explored using a dataset corresponding to an integrated luminosity of 4.7 fb−1. No excess of events beyond expectations from Standard Model processes is observed, and limits are set on large extra dimensions and the pair production of dark matter particles

Monitoring and data quality assessment of the ATLAS liquid argon calorimeter

The liquid argon calorimeter is a key component of the ATLAS detector installed at the CERN Large Hadron Collider. The primary purpose of this calorimeter is the measurement of electron and photon kinematic properties. It also provides a crucial input for measuring jets and missing transverse momentum. An advanced data monitoring procedure was designed to quickly identify issues that would affect detector performance and ensure that only the best quality data are used for physics analysis. This article presents the validation procedure developed during the 2011 and 2012 LHC data-taking periods, in which more than 98% of the proton-proton luminosity recorded by ATLAS at a centre-of-mass energy of 7-8 TeV had calorimeter data quality suitable for physics analysis

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s=7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb(-1) of root s = 7 TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results. (C) 2012 CERN. Published by Elsevier B.V. All rights reserved

Muon reconstruction efficiency and momentum resolution of the ATLAS experiment in proton–proton collisions at s√=7 TeV in 2010

This paper presents a study of the performance of the muon reconstruction in the analysis of proton?proton collisions at s√=7 TeV at the LHC, recorded by the ATLAS detector in 2010. This performance is described in terms of reconstruction and isolation efficiencies and momentum resolutions for different classes of reconstructed muons. The results are obtained from an analysis of J/ψ meson and Z boson decays to dimuons, reconstructed from a data sample corresponding to an integrated luminosity of 40 pb−1 . The measured performance is compared to Monte Carlo predictions and deviations from the predicted performance are discussed.Fil: Alconada Verzini, María Josefina

Drons col·laboratius

La robòtica col·laborativa és senzillament robots dissenyats per dur a terme treballs de col·laboració amb els humans. Els robots col·laboratius o cobots són cada cop més utilitzats a les indústries. La robòtica col·laborativa és un dels àmbits d'actualitat en aquests moments. Però també és un dels més interessants en més d'un sentit. Com es comuniquen dos drons autònoms que col·laboren per fer una tasca? Com són aquests missatges que s'envien? Que poden fer que no podrien fer sols? Aquestes són algunes de les preguntes que ens volem respondre en aquest projecte. En aquest treball es presenta un disseny i implementació de dos drons terrestres que es comuniquen per col·laborar entre ells per resoldre una tasca.Collaborative robotics is simply robots designed to perform collaborative work with humans. Collaborative robots or cobots are increasingly used in industries. Collaborative robotics is one of the current topics now. But it is also one of the most interesting in more ways than one. How do two autonomous drones that collaborate to perform a task communicate? How are these messages sent? What can they do that they could not do alone? These are some of the questions we want to answer in this project. This work presents a design and implementation of two ground drones that communicate to collaborate with each other to solve a task.La robótica colaborativa es sencillamente robots diseñados para llevar a cabo trabajos de colaboración con los humanos. Los robots colaborativos o cobots son cada vez más utilizados en las industrias. La robótica colaborativa es uno de los ámbitos de actualidad. Pero también es uno de los más interesantes en más de un sentido. ¿Cómo se comunican drones autónomos que colaboran para hacer una tarea? ¿Cómo son estos mensajes que es envían? ¿Qué pueden hacer que no lo podrían hacer solos? Estas son algunas de las preguntas que queremos responder con este proyecto. En este trabajo se presenta un diseño e implementación de dos drones terrestres que se comunican para colaborar entre ellos para resolver una tarea

Environmental variation is a major predictor of global trait turnover in mammals

Aim: To evaluate how environment and evolutionary history interact to influence global patterns of mammal trait diversity (a combination of 14 morphological and life-history traits). Location: The global terrestrial environment. Taxon: Terrestrial mammals. Methods: We calculated patterns of spatial turnover for mammalian traits and phylogenetic lineages using the mean nearest taxon distance. We then used a variance partitioning approach to establish the relative contribution of trait conservatism, ecological adaptation and clade specific ecological preferences on global trait turnover. Results: We provide a global scale analysis of trait turnover across mammalian terrestrial assemblages, which demonstrates that phylogenetic turnover by itself does not predict trait turnover better than random expectations. Conversely, trait turnover is consistently more strongly associated with environmental variation than predicted by our null models. The influence of clade-specific ecological preferences, reflected by the shared component of phylogenetic turnover and environmental variation, was considerably higher than expectations. Although global patterns of trait turnover are dependent on the trait under consideration, there is a consistent association between trait turnover and environmental predictive variables, regardless of the trait considered. Main conclusions: Our results suggest that changes in phylogenetic composition are not always coupled with changes in trait composition on a global scale and that environmental conditions are strongly associated with patterns of trait composition across species assemblages, both within and across phylogenetic clades

Environmental variation is a major predictor of global trait turnover in mammals

Aim: To evaluate how environment and evolutionary history interact to influence global patterns of mammal trait diversity (a combination of 14 morphological and life-history traits). Location: The global terrestrial environment.Taxon: Terrestrial mammals. Methods: We calculated patterns of spatial turnover for mammalian traits and phylogenetic lineages using the mean nearest taxon distance. We then used a variance partitioning approach to establish the relative contribution of trait conservatism, ecological adaptation and clade specific ecological preferences on global trait turnover.Results: We provide a global scale analysis of trait turnover across mammalian terrestrial assemblages, which demonstrates that phylogenetic turnover by itself does not predict trait turnover better than random expectations. Conversely, trait turnover is consistently more strongly associated with environmental variation than predicted by our null models. The influence of clade-specific ecological preferences, reflected by the shared component of phylogenetic turnover and environmental variation, was considerably higher than expectations. Although global patterns of trait turnover are dependent on the trait under consideration, there is a consistent association between trait turnover and environmental predictive variables, regardless of the trait considered.Main conclusions: Our results suggest that changes in phylogenetic composition are not always coupled with changes in trait composition on a global scale and that environmental conditions are strongly associated with patterns of trait composition across species assemblages, both within and across phylogenetic clades.</p