Higgs boson production via vector-like top-partner decays: diphoton or multilepton plus multijets channels at the LHC

We first build a minimal model of vector-like quarks where the dominant Higgs boson production process at LHC -- the gluon fusion -- can be significantly suppressed, being motivated by the recent stringent constraints from the search for direct Higgs production over a wide Higgs mass range. Within this model, compatible with the present experimental constraints on direct Higgs searches, we demonstrate that the Higgs ($h$) production via a heavy vector-like top-partner ($t_2$) decay, $pp \to t_2 \bar t_2$, $t_2\to t h$, allows to discover a Higgs boson at the LHC and measure its mass, through the decay channels $h\to \gamma\gamma$ or $h\to ZZ$. We also comment on the recent hint in LHC data from a possible $\sim 125$ GeV Higgs scalar, in the presence of heavy vector-like top quarks.Comment: 14 pages, 8 figure

Application of large area SiPMs for the readout of a plastic scintillator based timing detector

In this study an array of eight 6 mm x 6 mm area SiPMs was coupled to the end of a long plastic scintillator counter which was exposed to a 2.5 GeV/c muon beam at the CERN PS. Timing characteristics of bars with dimensions 150 cm x 6 cm x 1 cm and 120 cm x 11 cm x 2.5 cm have been studied. An 8-channel SiPM anode readout ASIC (MUSIC R1) based on a novel low input impedance current conveyor has been used to read out and amplify SiPMs independently and sum the signals at the end. Prospects for applications in large-scale particle physics detectors with timing resolution below 100 ps are provided in light of the results

Application of large area SiPMs for the readout of a plastic scintillator based timing detector

In this study an array of eight 6 mm x 6 mm area SiPMs was coupled to the end of a long plastic scintillator counter which was exposed to a 2.5 GeV/c muon beam at the CERN PS. Timing characteristics of bars with dimensions 150 cm x 6 cm x 1 cm and 120 cm x 11 cm x 2.5 cm have been studied. An 8-channel SiPM anode readout ASIC (MUSIC R1) based on a novel low input impedance current conveyor has been used to read out and amplify SiPMs independently and sum the signals at the end. Prospects for applications in large-scale particle physics detectors with timing resolution below 100 ps are provided in light of the results

Numerical Simulation of High Frequency Wave Coupling within a Hall Thruster

A 2-dimensional Hall thruster simulation has been developed in the axial-azimuthal coordinate plane. The goal of this simulation is to numerically model high frequency plasma waves within the discharge channel of the Hall thruster, and study the contribution of these waves to the time-averaged axial electron drift. This model uses a continuum (fluid) representation for both the electrons and ions. In order to simulate oscillations in the electron field it was necessary to model the electrons dynamically, as opposed to assuming a steady state solution at each time step. The electron momentum equations also include electron inertia terms that are normally neglected in typical Hall thruster models. These inertia terms provide a wave coupling mechanism between axially and azimuthally propagating waves. This numerical model was able to reproduce two dominant high frequency plasma oscillations in the Hall thruster: a 74MHz Kelvin-Helmholtz type shearing instability, and a 7MHz oscillation in the plasma density that has also been observed experimentally. The simulation was successful at predicting the axial electron drift in good agreement with experiment. The results of this study suggest that the plasma oscillations play a dominant role in the electron transport process. In particular, contributions to the electron transport resulting from perturbations in the azimuthal electron velocity were found to be greater than 300% of classical collisional transport

Effects of Residue Background Events in Direct Dark Matter Detection Experiments on the Determination of the WIMP Mass

In the earlier work on the development of a model-independent data analysis method for determining the mass of Weakly Interacting Massive Particles (WIMPs) by using measured recoil energies from direct Dark Matter detection experiments directly, it was assumed that the analyzed data sets are background-free, i.e., all events are WIMP signals. In this article, as a more realistic study, we take into account a fraction of possible residue background events, which pass all discrimination criteria and then mix with other real WIMP-induced events in our data sets. Our simulations show that, for the determination of the WIMP mass, the maximal acceptable fraction of residue background events in the analyzed data sets of O(50) total events is ~20%, for background windows of the entire experimental possible energy ranges, or in low energy ranges; while, for background windows in relatively higher energy ranges, this maximal acceptable fraction of residue background events can not be larger than ~10%. For a WIMP mass of 100 GeV with 20% background events in the windows of the entire experimental possible energy ranges, the reconstructed WIMP mass and the 1-sigma statistical uncertainty are ~97 GeV^{+61%}_{-35%} (~94 GeV^{+55%}_{-33%} for background-free data sets).Comment: 27 pages, 22 eps figures; v2: revised version for publication, references added and update

A Randomized Controlled Trial Translating the Diabetes Prevention Program to a University Worksite, Ohio, 2012-2014

INTRODUCTION: Working adults spend much time at the workplace, an ideal setting for wellness programs targeting weight loss and disease prevention. Few randomized trials have evaluated the efficacy of worksite diabetes prevention programs. This study evaluated the efficacy of a worksite lifestyle intervention on metabolic and behavioral risk factors compared with usual care. METHODS: A pretest-posttest control group design with 3-month follow-up was used. Participants with prediabetes were recruited from a university worksite and randomized to receive a 16-week lifestyle intervention (n = 35) or usual care (n = 34). Participants were evaluated at baseline, postintervention, and 3-month follow-up. Dietary intake was measured by a food frequency questionnaire and level of physical activity by accelerometers. Repeated measures analysis of variance compared the change in outcomes between and within groups. RESULTS: Mean (standard error [SE]) weight loss was greater in the intervention (-5.5% [0.6%]) than in the control (-0.4% [0.5%]) group (P < .001) postintervention and was sustained at 3-month follow-up (P < .001). Mean (SE) reductions in fasting glucose were greater in the intervention (-8.6 [1.6] mg/dL) than in the control (-3.7 [1.6] mg/dL) group (P = .02) postintervention; both groups had significant glucose reductions at 3-month follow-up (P < .001). In the intervention group, the intake of total energy and the percentage of energy from all fats, saturated fats, and trans fats decreased, and the intake of dietary fiber increased (all P < .01) postintervention. CONCLUSION: The worksite intervention improved metabolic and behavioral risk factors among employees with prediabetes. The long-term impact on diabetes prevention and program sustainability warrant further investigation

Malaria prophylaxis policy for travellers from Europe to the Indian Sub Continent

Analysis of malaria imported into eight European countries from the Indian sub-continent (ISC) (India, Pakistan, Bangladesh and Sri Lanka) led to a consensus statement on the use of chemoprophylaxis within TropNetEurop. The proportion of cases from the ISC in 2004 ranged from 1.4%–4.6% of total imported cases. Plasmodium falciparum cases reported from the eight countries was only 23 (13% of all cases from the region). Total malaria reports between 1999–2004 fell from 317 to 180. The risk of malaria in UK residents visiting the region was > 1 case per 1,000 years exposed. The group recommended non-selective prescribing of chemoprophylaxis for visitors to India, Pakistan, Bangladesh and Sri Lanka should be dropped

Clinical prediction rules for adverse evolution in patients with COVID-19 by the Omicron variant

Objective: We identify factors related to SARS-CoV-2 infection linked to hospitalization, ICU admission, and mortality and develop clinical prediction rules. Methods: Retrospective cohort study of 380,081 patients with SARS-CoV-2 infection from March 1, 2020 to January 9, 2022, including a subsample of 46,402 patients who attended Emergency Departments (EDs) having data on vital signs. For derivation and external validation of the prediction rule, two different periods were considered: before and after emergence of the Omicron variant, respectively. Data collected included sociodemographic data, COVID-19 vaccination status, baseline comorbidities and treatments, other background data and vital signs at triage at EDs. The predictive models for the EDs and the whole samples were developed using multivariate logistic regression models using Lasso penalization. Results: In the multivariable models, common predictive factors of death among EDs patients were greater age; being male; having no vaccination, dementia; heart failure; liver and kidney disease; hemiplegia or paraplegia; coagulopathy; interstitial pulmonary disease; malignant tumors; use chronic systemic use of steroids, higher temperature, low O2 saturation and altered blood pressure-heart rate. The predictors of an adverse evolution were the same, with the exception of liver disease and the inclusion of cystic fibrosis. Similar predictors were found to be related to hospital admission, including liver disease, arterial hypertension, and basal prescription of immunosuppressants. Similarly, models for the whole sample, without vital signs, are presented. Conclusions: We propose risk scales, based on basic information, easily-calculable, high-predictive that also function with the current Omicron variant and may help manage such patients in primary, emergency, and hospital care. Keywords: COVID-19; Clinical decision rules; Health care; Outcome assessment; SARS-CoV-2

ATLAS Infrastructure

This document describes the civil engineering and infrastructure work done on the surface and underground for the ATLAS experiment at point 1 of the LHC ring

Relevance of comorbidities for main outcomes during different periods of the COVID-19 pandemic

Background: Throughout the evolution of the COVID-19 pandemic, the severity of the disease has varied. The aim of this study was to determine how patients' comorbidities affected and were related to, different outcomes during this time. Methods: Retrospective cohort study of all patients testing positive for SARS-CoV-2 infection between March 1, 2020, and January 9, 2022. We extracted sociodemographic, basal comorbidities, prescribed treatments, COVID-19 vaccination data, and outcomes such as death and admission to hospital and intensive care unit (ICU) during the different periods of the pandemic. We used logistic regression to quantify the effect of each covariate in each outcome variable and a random forest algorithm to select the most relevant comorbidities. Results: Predictors of death included having dementia, heart failure, kidney disease, or cancer, while arterial hypertension, diabetes, ischemic heart, cerebrovascular, peripheral vascular diseases, and leukemia were also relevant. Heart failure, dementia, kidney disease, diabetes, and cancer were predictors of adverse evolution (death or ICU admission) with arterial hypertension, ischemic heart, cerebrovascular, peripheral vascular diseases, and leukemia also relevant. Arterial hypertension, heart failure, diabetes, kidney, ischemic heart diseases, and cancer were predictors of hospitalization, while dyslipidemia and respiratory, cerebrovascular, and peripheral vascular diseases were also relevant. Conclusions: Preexisting comorbidities such as dementia, cardiovascular and renal diseases, and cancers were those most related to adverse outcomes. Of particular note were the discrepancies between predictors of adverse outcomes and predictors of hospitalization and the fact that patients with dementia had a lower probability of being admitted in the first wave