Modulation of Sn concentration in ZnO nanorod array: intensification on the conductivity and humidity sensing properties

Tin (Sn)-doped zinc oxide (ZnO) nanorod arrays (TZO) were synthesized onto aluminum-doped ZnO-coated glass substrate via a facile sonicated sol–gel immersion method for humidity sensor applications. These nanorod arrays were grown at different Sn concentrations ranging from 0.6 to 3 at.%. X-ray diffraction patterns showed that the deposited TZO arrays exhibited a wurtzite structure. The stress/strain condition of the ZnO film metamorphosed from tensile strain/compressive stress to compressive strain/tensile stress when the Sn concentrations increased. Results indicated that 1 at.% Sn doping of TZO, which has the lowest tensile stress of 0.14 GPa, generated the highest conductivity of 1.31 S cm− 1. In addition, 1 at.% Sn doping of TZO possessed superior sensitivity to a humidity of 3.36. These results revealed that the optimum performance of a humidity-sensing device can be obtained mainly by controlling the amount of extrinsic element in a ZnO film

Impact of the Covid-19 pandemic on perinatal mental health (Riseup-PPD-COVID-19): protocol for an international prospective cohort study

Background: Corona Virus Disease 19 (COVID-19) is a new pandemic, declared a public health emergency by the World Health Organization, which could have negative consequences for pregnant and postpartum women. The scarce evidence published to date suggests that perinatal mental health has deteriorated since the COVID-19 outbreak. However, the few studies published so far have some limitations, such as a cross-sectional design and the omission of important factors for the understanding of perinatal mental health, including governmental restriction measures and healthcare practices implemented at the maternity hospitals. Within the Riseup-PPD COST Action, a study is underway to assess the impact of COVID-19 in perinatal mental health. The primary objectives are to (1) evaluate changes in perinatal mental health outcomes; and (2) determine the risk and protective factors for perinatal mental health during the COVID-19 pandemic. Additionally, we will compare the results between the countries participating in the study. Methods: This is an international prospective cohort study, with a baseline and three follow-up assessments over a six-month period. It is being carried out in 11 European countries (Albania, Bulgaria, Cyprus, France, Greece, Israel, Malta, Portugal, Spain, Turkey, and the United Kingdom), Argentina, Brazil and Chile. The sample consists of adult pregnant and postpartum women (with infants up to 6 months of age). The assessment includes measures on COVID-19 epidemiology and public health measures (Oxford COVID-19 Government Response Tracker dataset), Coronavirus Perinatal Experiences (COPE questionnaires), psychological distress (BSI-18), depression (EPDS), anxiety (GAD-7) and post-traumatic stress symptoms (PTSD checklist for DSM-V). Discussion: This study will provide important information for understanding the impact of the COVID-19 pandemic on perinatal mental health and well-being, including the identification of potential risk and protective factors by implementing predictive models using machine learning techniques. The findings will help policymakers develop suitable guidelines and prevention strategies for perinatal mental health and contribute to designing tailored mental health interventions. Trial registration: ClinicalTrials.gov Identifier: NCT04595123.The project is part of the COST Action Riseup-PPD CA 18138 and was supported by COST under COST Action Riseup-PPD CA18138; also, by the Spanish Ministry of Health, the Institute of Health Carlos III, and the European Regional Development Fund «Una manera de hacer Europa» by the Prevention and Health Promotion Research Network ‘redIAPP’ (RD16/0007). Raquel Costa is supported by the FSE and FCT under an individual Post-Doctoral Grant SFRH/BPD/117597/2016. Rena Bina and Drorit Levy received funding from the Bar-Ilan Dangoor Centre for Personalized Medicine, Israel. Ana Mesquita is supported from the Portuguese Foundation for Science and Technology (FCT) and from EU through the European Social Fund and from the Human Potential Operational Program - IF/00750/2015. Ana Osório received financial support from CAPES/Proex no. 0653/2018 and CAPES/PrInt grant no. 88887.310343/2018-00.The funders of the study had no role in the study design or the writing the protocol. The corresponding author had final responsibility for the decision to submit for publication

A Communal Bacterial Adhesin Anchors Biofilm and Bystander Cells to Surfaces

While the exopolysaccharide component of the biofilm matrix has been intensively studied, much less is known about matrix-associated proteins. To better understand the role of these proteins, we undertook a proteomic analysis of the V. cholerae biofilm matrix. Here we show that the two matrix-associated proteins, Bap1 and RbmA, perform distinct roles in the biofilm matrix. RbmA strengthens intercellular attachments. In contrast, Bap1 is concentrated on surfaces where it serves to anchor the biofilm and recruit cells not yet committed to the sessile lifestyle. This is the first example of a biofilm-derived, communally synthesized conditioning film that stabilizes the association of multilayer biofilms with a surface and facilitates recruitment of planktonic bystanders to the substratum. These studies define a novel paradigm for spatial and functional differentiation of proteins in the biofilm matrix and provide evidence for bacterial cooperation in maintenance and expansion of the multilayer biofilm

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

<p>Abstract</p> <p>Background</p> <p>The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student's-<it>t </it>model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student's-<it>t </it>(BS<it>t</it>) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.</p> <p>Methods</p> <p>In the simulation study, bivariate residuals were generated using Student's-<it>t </it>distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student's-<it>t </it>or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student's-<it>t </it>distributions with unknown degrees of freedom.</p> <p>Results</p> <p>Posterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student's-<it>t </it>error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student's-<it>t </it>model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.</p> <p>Conclusions</p> <p>Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.</p> <p>Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.</p

Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome after renal transplantation in the United States

BACKGROUND: The incidence and risk factors for diabetic ketoacidosis (diabetic ketoacidosis) and hyperglycemic hyperosmolar syndrome (hyperglycemic hyperosmolar syndrome, previously called non-ketotic hyperosmolar coma) have not been reported in a national population of renal transplant (renal transplantation) recipients. METHODS: We performed a historical cohort study of 39,628 renal transplantation recipients in the United States Renal Data System between 1 July 1994 and 30 June 1998, followed until 31 Dec 1999. Outcomes were hospitalizations for a primary diagnosis of diabetic ketoacidosis (ICD-9 code 250.1x) and hyperglycemic hyperosmolar syndrome (code 250.2x). Cox Regression analysis was used to calculate adjusted hazard ratios for time to hospitalization for diabetic ketoacidosis or hyperglycemic hyperosmolar syndrome. RESULTS: The incidence of diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome were 33.2/1000 person years (PY) and 2.7/1000 PY respectively for recipients with a prior diagnosis of diabetes mellitus (DM), and 2.0/1000 PY and 1.1/1000 PY in patients without DM. In Cox Regression analysis, African Americans (AHR, 2.71, 95 %CI, 1.96–3.75), females, recipients of cadaver kidneys, patients age 33–44 (vs. >55), more recent year of transplant, and patients with maintenance TAC (tacrolimus, vs. cyclosporine) had significantly higher risk of diabetic ketoacidosis. However, the rate of diabetic ketoacidosis decreased more over time in TAC users than overall. Risk factors for hyperglycemic hyperosmolar syndrome were similar except for the significance of positive recipient hepatitis C serology and non-significance of female gender. Both diabetic ketoacidosis (AHR, 2.44, 95% CI, 2.10–2.85, p < 0.0001) and hyperglycemic hyperosmolar syndrome (AHR 1.87, 95% CI, 1.22–2.88, p = 0.004) were independently associated with increased mortality. CONCLUSIONS: We conclude that diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome were associated with increased risk of mortality and were not uncommon after renal transplantation. High-risk groups were identified

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques