344 research outputs found

    Back To The Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection

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    Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable performance on specific signatures such as di-jet resonances, their application in a more model-agnostic manner requires dealing with a larger number of potentially noisy input features. In this paper, we show that using boosted decision trees as classifiers in weakly supervised anomaly detection gives superior performance compared to deep neural networks. Boosted decision trees are well known for their effectiveness in tabular data analysis. Our results show that they not only offer significantly faster training and evaluation times, but they are also robust to a large number of noisy input features. By using advanced gradient boosted decision trees in combination with ensembling techniques and an extended set of features, we significantly improve the performance of weakly supervised methods for anomaly detection at the LHC. This advance is a crucial step towards a more model-agnostic search for new physics.Comment: 11 pages, 9 figure

    Score rectification for online assessments in robot-assisted arm rehabilitation

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    Relative comparison of clinical scores to measure the effectiveness of neuro-rehabilitation therapy is possible through a series of discrete measurements during the rehabilitation period within specifically designed task environments. Robots allow quantitative, continuous measurement of data. Resulting robotic scores are also only comparable within similar context, e.g. type of task. We propose a method to decouple these scores from their respective context through functional orthogonalization and compensation of the compounding factors based on a data-driven sensitivity analysis of the user performance. The method was validated for the established accuracy score with variable arm weight support, provoked muscle fatigue and different task directions on 6 participants of our arm exoskeleton group on the ANYexo robot. In the best case, the standard deviation of the assessed score in changing context could be reduced by a factor of 3.2. Therewith, we paved the way to context-independent, quantitative online assessments, recorded autonomously with robots.ISSN:0178-2312ISSN:2196-677

    miRNAs, from Evolutionary Junk to Possible Prognostic Markers and Therapeutic Targets in COVID-19

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    The COVID-19 pandemic has been a public health issue around the world in the last few years. Currently, there is no specific antiviral treatment to fight the disease. Thus, it is essential to highlight possible prognostic predictors that could identify patients with a high risk of developing complications. Within this framework, miRNA biomolecules play a vital role in the genetic regulation of various genes, principally, those related to the pathophysiology of the disease. Here, we review the interaction of host and viral microRNAs with molecular and cellular elements that could potentiate the main pulmonary, cardiac, renal, circulatory, and neuronal complications in COVID-19 patients. miR-26a, miR-29b, miR-21, miR-372, and miR-2392, among others, have been associated with exacerbation of the inflammatory process, increasing the risk of a cytokine storm. In addition, increased expression of miR-15b, -199a, and -491 are related to the prognosis of the disease, and miR-192 and miR-323a were identified as clinical predictors of mortality in patients admitted to the intensive care unit. Finally, we address miR-29, miR-122, miR-155, and miR-200, among others, as possible therapeutic targets. However, more studies are required to confirm these findings

    Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

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    International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum pTp_\mathrm{T} and rapidity yy. The measurement is performed using proton-proton collision data at s\sqrt{s} = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb1^{-1}. The jets are reconstructed with the anti-kTk_\mathrm{T} algorithm using a distance parameter of RR = 0.4, within the rapidity interval y\lvert y\rvert<\lt 2, and across the kinematic range 0.06 <\ltpTp_\mathrm{T}<\lt 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling αS\alpha_\mathrm{S}

    Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

    No full text
    International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum pTp_\mathrm{T} and rapidity yy. The measurement is performed using proton-proton collision data at s\sqrt{s} = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb1^{-1}. The jets are reconstructed with the anti-kTk_\mathrm{T} algorithm using a distance parameter of RR = 0.4, within the rapidity interval y\lvert y\rvert<\lt 2, and across the kinematic range 0.06 <\ltpTp_\mathrm{T}<\lt 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling αS\alpha_\mathrm{S}

    Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

    No full text
    International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum pTp_\mathrm{T} and rapidity yy. The measurement is performed using proton-proton collision data at s\sqrt{s} = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb1^{-1}. The jets are reconstructed with the anti-kTk_\mathrm{T} algorithm using a distance parameter of RR = 0.4, within the rapidity interval y\lvert y\rvert<\lt 2, and across the kinematic range 0.06 <\ltpTp_\mathrm{T}<\lt 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling αS\alpha_\mathrm{S}

    Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

    No full text
    International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum pTp_\mathrm{T} and rapidity yy. The measurement is performed using proton-proton collision data at s\sqrt{s} = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb1^{-1}. The jets are reconstructed with the anti-kTk_\mathrm{T} algorithm using a distance parameter of RR = 0.4, within the rapidity interval y\lvert y\rvert<\lt 2, and across the kinematic range 0.06 <\ltpTp_\mathrm{T}<\lt 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling αS\alpha_\mathrm{S}

    Measurement of inclusive and differential cross sections for single top quark production in association with a W boson in proton-proton collisions at s \sqrt{s} = 13 TeV

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    International audienceMeasurements of the inclusive and normalised differential cross sections are presented for the production of single top quarks in association with a W boson in proton-proton collisions at a centre-of-mass energy of 13 TeV. The data used were recorded with the CMS detector at the LHC during 2016–2018, and correspond to an integrated luminosity of 138 fb1^{−1}. Events containing one electron and one muon in the final state are analysed. For the inclusive measurement, a multivariate discriminant, exploiting the kinematic properties of the events is used to separate the signal from the dominant tt \textrm{t}\overline{\textrm{t}} background. A cross section of 79.2±0.9(stat)8.0+7.7(syst)±1.2(lumi) 79.2\pm 0.9{\left(\textrm{stat}\right)}_{-8.0}^{+7.7}\left(\textrm{syst}\right)\pm 1.2\left(\textrm{lumi}\right) pb is obtained, consistent with the predictions of the standard model. For the differential measurements, a fiducial region is defined according to the detector acceptance, and the requirement of exactly one jet coming from the fragmentation of a bottom quark. The resulting distributions are unfolded to particle level and agree with the predictions at next-to-leading order in perturbative quantum chromodynamics.[graphic not available: see fulltext
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