Publications by authors named "A Vicini"
Article Synopsis
- The study analyzes the compatibility of Higgs boson mass measurements from several experiments (ATLAS, LHCb, CDF, D0) using a coherent framework that accounts for theory uncertainties.
- The combination of these measurements with recent parton distribution functions (PDF) indicates low compatibility with global Drell-Yan results, with CT18 being the most compatible due to its larger uncertainties.
- Removing the CDF measurement yields a higher probability of compatibility (91%) and results in a different Higgs boson mass value compared to the CDF's own measurement using the same PDF set.
Article Synopsis
- * It discusses the theoretical predictions of this observable, including its robustness at various orders of Quantum Chromodynamics (QCD) and its ability to provide a reliable measurement with minimal uncertainty.
- * The observable's inclusive nature makes it beneficial for experiments, particularly for analyzing detector effects, and it could significantly improve the experimental accuracy of the -boson mass measurement at the Large Hadron Collider (LHC).
Background: Plastics have conveyed great benefits to humanity and made possible some of the most significant advances of modern civilization in fields as diverse as medicine, electronics, aerospace, construction, food packaging, and sports. It is now clear, however, that plastics are also responsible for significant harms to human health, the economy, and the earth's environment. These harms occur at every stage of the plastic life cycle, from extraction of the coal, oil, and gas that are its main feedstocks through to ultimate disposal into the environment.
View Article and Find Full Text PDFLiquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics experiments have become increasingly popular because of the wide range of metabolites that can be analyzed and the possibility to measure novel compounds. LC-MS instrumentation and analysis conditions can differ substantially among laboratories and experiments, thus resulting in non-standardized datasets demanding customized annotation workflows. We present an ecosystem of R packages, centered around the , and packages that together provide a modular infrastructure for the annotation of untargeted metabolomics data.
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