Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

The association between skin color/race and health indicators in elderly Brazilians: a study based on the Brazilian National Household Sample Survey (2008)

This study analyzed racial inequalities in health in 18,684 elderly Brazilians 65 years or older, interviewed in the National Household Sample Survey in 2008 (PNAD 2008), and who reported their color/race as white, brown, or black. Associations were estimated between self-rated health status, functional incapacity, and number of chronic conditions according to crude and adjusted regression analyses (α = 0.01). The majority of the elderly were white (56.2%). In the adjusted analysis, brown color/races was associated with worse self-rated health status (OR = 1.11; 95%CI: 1.03-1.18) and black color/race was associated with more chronic diseases (PR = 1.07; 95%CI: 1.02-1.13). Brown color/race appeared as a protective factor against functional incapacity. When brown and black elderly were combined in one category (“black”), “black” elderly continued to show worse self-rated health status (OR = 1.09; 95%CI: 1.02-1.16) and lower odds of functional incapacity (OR = 0.83; 95%CI: 0.76-0.92). “Black” color/race lost the association with number of chronic diseases. Color/race explained part of the health inequalities in elderly Brazilians, but other socioeconomic variables had a more striking effect

Self-rated health in urban adults, perceptions of the physical and social environment, and reported comorbidities: The BH Health Study

Abstract This study assesses the prevalence of poor self-rated health and investigates its association with individual and environmental characteristics in adults with and without reported morbidity. A household survey assessed 4,048 adults in two districts of Belo Horizonte, Minas Gerais State, Brazil. We used Poisson regression with robust variance stratified by the presence of reported morbidity. Prevalence of poor self-rated health was 29.9% (42.6% in those with morbidity and 13.1% in the group without morbidity). All assessed domains were associated with self-rated health in subjects with reported morbidity. In the group without reported morbidity, the following were associated with self-rated health: social environment, socio-demographic factors, lifestyle, and psychological health. Perceived problems in the environment were associated with poor self-rated health in both groups, even after hierarchical adjustment. The results suggest the importance of investigating self-rated health stratified by reported morbidity and reinforce the need to include variables that characterize the physical and social environment

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging

ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton-proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 fb$^{-1}$ of collisions at a centre-of-mass energy of $\sqrt{s}$ = 8 TeV, although in some case an additional 4.7 fb$^{-1}$ of collision data at $\sqrt{s}$ = 7 TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models