Search for the standard model Higgs boson decaying to a bb pair in events with one charged lepton and large missing transverse energy using the full CDF data set

We present a search for the standard model Higgs boson produced in association with a W boson in sqrt(s) = 1.96 TeV p-pbar collision data collected with the CDF II detector at the Tevatron corresponding to an integrated luminosity of 9.45 fb-1. In events consistent with the decay of the Higgs boson to a bottom-quark pair and the W boson to an electron or muon and a neutrino, we set 95% credibility level upper limits on the WH production cross section times the H->bb branching ratio as a function of Higgs boson mass. At a Higgs boson mass of 125 GeV/c2 we observe (expect) a limit of 4.9 (2.8) times the standard model value.Comment: Submitted to Phys. Rev. Lett (v2 contains clarifications suggested by PRL

Search for the standard model Higgs boson decaying to a bbˉb\bar{b} pair in events with no charged leptons and large missing transverse energy using the full CDF data set

We report on a search for the standard model Higgs boson produced in association with a vector boson in the full data set of proton-antiproton collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II detector at the Tevatron, corresponding to an integrated luminosity of 9.45 fb$^{-1}$. We consider events having no identified charged lepton, a transverse energy imbalance, and two or three jets, of which at least one is consistent with originating from the decay of a $b$ quark. We place 95% credibility level upper limits on the production cross section times standard model branching fraction for several mass hypotheses between 90 and $150 \mathrm{GeV}/c^2$. For a Higgs boson mass of $125 \mathrm{GeV}/c^2$, the observed (expected) limit is 6.7 (3.6) times the standard model prediction.Comment: Accepted by Phys. Rev. Let

Search for the standard model Higgs boson decaying to a bb pair in events with two oppositely-charged leptons using the full CDF data set

We present a search for the standard model Higgs boson produced in association with a Z boson in data collected with the CDF II detector at the Tevatron, corresponding to an integrated luminosity of 9.45/fb. In events consistent with the decay of the Higgs boson to a bottom-quark pair and the Z boson to electron or muon pairs, we set 95% credibility level upper limits on the ZH production cross section times the H -> bb branching ratio as a function of Higgs boson mass. At a Higgs boson mass of 125 GeV/c^2 we observe (expect) a limit of 7.1 (3.9) times the standard model value.Comment: To be submitted to Phys. Rev. Let

Measurement of the difference of CP-violating asymmetries in D0 -> K+K- and D0 ->pi+pi- decays at CDF

We report a measurement of the difference (Delta Acp) between time-integrated CP--violating asymmetries in D0-> K+ K- and D0-> pi+pi- decays reconstructed in the full data set of proton-antiproton collisions collected by the Collider Detector at Fermilab, corresponding to 9.7 fb-1 of integrated luminosity. The strong decay D*+->D0 pi+ is used to identify the charm meson at production as D0 or anti-D0. We measure Delta Acp = [-0.62 +- 0.21 (stat) +- 0.10 (syst)] %, which differs from zero by 2.7 Gaussian standard deviations.This result supports similar evidence for CP violation in charm-quark decays obtained in proton-proton collisions.Comment: Phys. Rev. Lett. 109, 111801 (2012

Combined Tevatron upper limit on gg->H->W+W- and constraints on the Higgs boson mass in fourth-generation fermion models

Report number: FERMILAB-PUB-10-125-EWe combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg->H->W+W- in p=pbar collisions at the Fermilab Tevatron Collider at sqrt{s}=1.96 TeV. With 4.8 fb-1 of integrated luminosity analyzed at CDF and 5.4 fb-1 at D0, the 95% Confidence Level upper limit on \sigma(gg->H) x B(H->W+W-) is 1.75 pb at m_H=120 GeV, 0.38 pb at m_H=165 GeV, and 0.83 pb at m_H=200 GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% Confidence Level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.We combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg→H→W+W- in pp̅ collisions at the Fermilab Tevatron Collider at √s=1.96  TeV. With 4.8  fb-1 of integrated luminosity analyzed at CDF and 5.4  fb-1 at D0, the 95% confidence level upper limit on σ(gg→H)×B(H→W+W-) is 1.75 pb at mH=120  GeV, 0.38 pb at mH=165  GeV, and 0.83 pb at mH=200  GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% confidence level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.Peer reviewe

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers’ Mental Workload Classification

In the pursuit of reducing traffic accidents, drivers’ mental workload (MWL) has been considered as one of the vital aspects. To measure MWL in different driving situations Electroencephalography (EEG) of the drivers has been studied intensely. However, in the literature, mostly, manual analytic methods are applied to extract and select features from the EEG signals to quantify drivers’ MWL. Nevertheless, the amount of time and effort required to perform prevailing feature extraction techniques leverage the need for automated feature extraction techniques. This work investigates deep learning (DL) algorithm to extract and select features from the EEG signals during naturalistic driving situations. Here, to compare the DL based and traditional feature extraction techniques, a number of classifiers have been deployed. Results have shown that the highest value of area under the curve of the receiver operating characteristic (AUC-ROC) is 0.94, achieved using the features extracted by convolutional neural network autoencoder (CNN-AE) and support vector machine. Whereas, using the features extracted by the traditional method, the highest value of AUC-ROC is 0.78 with the multi-layer perceptron. Thus, the outcome of this study shows that the automatic feature extraction techniques based on CNN-AE can outperform the manual techniques in terms of classification accuracy

Modeling ZnS and ZnO Nanostructures: Structural, Electronic, and Optical Properties

We report the computational modeling of ZnS and ZnO nanostructures by defining realistic nanoparticle models ∼1.5 nm sized for each material and investigating their structural, electronic, and optical properties by means of DFT/TDDFT calculations. To provide a direct comparison of calculated data to experimentally characterized nanoparticles, 3D (ZnX)111 nanoclusters of prismatic shape have been set up starting from the bulk wurtzite (X = O, S), with two different saturation patterns of the polar surfaces. The investigated models have been optimized by means of CarParrinello molecular dynamics and local geometry optimization techniques. The investigated systems exhibit a well-opened HOMOLUMO energy gap, without any artificial intraband-gap states. TDDFT calculation of the lowest excitation energies are in excellent agreement, within 0.1-0.2 eV, with the experimental absorption onsets reported for similarly sized ZnO and ZnS nanoparticles (3.70 and 4.40 eV, respectively). We have also investigated the electronic structure of the considered nanoparticles, with reference to the valence band structure, finding calculated binding energies for the Zn d-shell to be only slightly displaced toward lower values compared to experimental values, possibly due to quantum confinement effects. This work provides the required computational framework for modeling ZnX and in general II-VI semiconductor nanomaterials, opening the way to simulation of ligand/semiconductor interactions