Hemisphere Mixing: a Fully Data-Driven Model of QCD Multijet Backgrounds for LHC Searches

A novel method is proposed here to precisely model the multi-dimensional features of QCD multi-jet events in hadron collisions. The method relies on the schematization of high-pT QCD processes as 2->2 reactions made complex by sub-leading effects. The construction of libraries of hemispheres from experimental data and the definition of a suitable nearest-neighbor-based association map allow for the generation of artificial events that reproduce with surprising accuracy the kinematics of the QCD component of original data, while remaining insensitive to small signal contaminations. The method is succinctly described and its performance is tested in the case of the search for the hh->bbbb process at the LHC.Comment: 4 pages plus header, 1 figure, proceedings of EPS 2017 Venic

Metabolic syndrome predictors of brain gray matter volume in an age-stratified community sample of 776 Mexican- American adults: Results from the genetics of brain structure image archive

Introduction: This project aimed to investigate the association between biometric components of metabolic syndrome (MetS) with gray matter volume (GMV) obtained with magnetic resonance imaging (MRI) from a large cohort of community-based adults (n = 776) subdivided by age and sex and employing brain regions of interest defined previously as the “Neural Signature of MetS” (NS-MetS). Methods: Lipid profiles, biometrics, and regional brain GMV were obtained from the Genetics of Brain Structure (GOBS) image archive. Participants underwent T1-weighted MR imaging. MetS components (waist circumference, fasting plasma glucose, triglycerides, HDL cholesterol, and blood pressure) were defined using the National Cholesterol Education Program Adult Treatment Panel III. Subjects were grouped by age: early adult (18–25 years), young adult (26–45 years), and middle-aged adult (46–65 years). Linear regression modeling was used to investigate associations between MetS components and GMV in five brain regions comprising the NS-MetS: cerebellum, brainstem, orbitofrontal cortex, right insular/limbic cluster and caudate. Results: In both men and women of each age group, waist circumference was the single component most strongly correlated with decreased GMV across all NS-MetS regions. The brain region most strongly correlated to all MetS components was the posterior cerebellum. Conclusion: The posterior cerebellum emerged as the region most significantly associated with MetS individual components, as the only region to show decreased GMV in young adults, and the region with the greatest variance between men and women. We propose that future studies investigating neurological effects of MetS and its comorbidities—namely diabetes and obesity—should consider the NS-MetS and the differential effects of age and sex

Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider

Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named “AMVA4NewPhysics” studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented along with the evaluation of their performances. © 2021 The Author(s

Price Fluctuations and the Use of Bitcoin: An Empirical Inquiry

Over recent years, interest has been growing in Bitcoin, an innovation that has the potential to play an important role in e-commerce and beyond. The aim of our paper is to provide a comprehensive empirical study of the payment and investment features of Bitcoin, and their implications for the conduct of e-commerce. Since network externality theory suggests that the value of a network and its take-up are interlinked, we investigate both adoption and price formation. We discover that its returns are driven primarily by Bitcoin’s popularity, the sentiment expressed in newspaper reports on cryptocurrency, and total number of transactions. The paper also reports on the first global survey of merchants who have adopted this technology, and we model the share of sales paid for with this alternative currency, using both ordinary and Tobit regressions. Our analysis examines how country-, customer-, and company-specific characteristics interact with the proportion of sales attributed to Bitcoin. We find that company features, use of other payment methods, customers’ knowledge about Bitcoin, and the size of both the official and unofficial economy are significant determinants. The results will be of interest to traders who seek to understand factors driving prices and will help to inform vendors as to the most favorable circumstances for adopting the currency for online transactions

A neural signature of metabolic syndrome

That metabolic syndrome (MetS) is associated with age‐related cognitive decline is well established. The neurobiological changes underlying these cognitive deficits, however, are not well understood. The goal of this study was to determine whether MetS is associated with regional differences in gray‐matter volume (GMV) using a cross‐sectional, between‐group contrast design in a large, ethnically homogenous sample. T1‐weighted MRIs were sampled from the genetics of brain structure (GOBS) data archive for 208 Mexican‐American participants: 104 participants met or exceeded standard criteria for MetS and 104 participants were age‐ and sex‐matched metabolically healthy controls. Participants ranged in age from 18 to 74 years (37.3 ± 13.2 years, 56.7% female). Images were analyzed in a whole‐brain, voxel‐wise manner using voxel‐based morphometry (VBM). Three contrast analyses were performed, a whole sample analysis of all 208 participants, and two post hoc half‐sample analyses split by age along the median (35.5 years). Significant associations between MetS and decreased GMV were observed in multiple, spatially discrete brain regions including the posterior cerebellum, brainstem, orbitofrontal cortex, bilateral caudate nuclei, right parahippocampus, right amygdala, right insula, lingual gyrus, and right superior temporal gyrus. Age, as shown in the post hoc analyses, was demonstrated to be a significant covariate. A further functional interpretation of the structures exhibiting lower GMV in MetS reflected a significant involvement in reward perception, emotional valence, and reasoning. Additional studies are needed to characterize the influence of MetS\u27s individual clinical components on brain structure and to explore the bidirectional association between GMV and MetS