Water vapour total columns from SCIAMACHY spectra in the 2.36 μm window

The potential of the shortwave infrared channel of the atmospheric spectrometer SCIAMACHY on Envisat to provide accurate measurements of total atmospheric water vapour columns is explored. It is shown that good quality results can be obtained for cloud free scenes above the continents using the Iterative Maximum Likelihood Method. In addition to the standard cloud filter employed in this method, further cloud screening is obtained by comparing simultaneously retrieved methane columns with values expected from models. A novel method is used to correct for the scattering effects introduced in the spectra by the ice layer on the detector window. The retrieved water vapour total vertical columns for the period 2003–2007 are compared with spatially and temporally collocated values from the European Centre for Mid-Range Weather Forecast (ECMWF) data. The observed differences for individual measurements have standard deviations not higher than 0.3 g/cm^2 and an absolute mean value smaller than 0.01 g/cm^2 with some regional excursions. The use of recently published spectroscopic data for water vapour led to a significant improvement in the agreement of the retrieved water vapour total columns and the values derived from ECMWF data. This analysis thus supports the superior quality of the new spectroscopic information using atmospheric data

The development and validation of a five-factor model of Sources of Self-Efficacy in clinical nursing education

Background: The aim of this study is to validate a newly developed nurses' self-efficacy sources inventory. We test the validity of a five-dimensional model of sources of self-efficacy, which we contrast with the traditional four-dimensional model based on Bandura’s theoretical concepts.Methods: Confirmatory factor analysis was used in the development of the newly developed self-efficacy measure. Model fit was evaluated based upon commonly recommended goodness-of-fit indices, including the χ2 of the model fit, the Root Mean Square Error of approximation (RMSEA), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual (SRMR), and the Bayesian Information Criterion (BIC).Results: All 22 items of the newly developed five-factor sources of self-efficacy have high factor loadings (range .40-.80). Structural equation modeling showed that a five-factor model is favoured over the four-factor model.Conclusions and implications: Results of this study show that differentiation of the vicarious experience source into a peer- and expert based source reflects better how nursing students develop self-efficacy beliefs. This has implications for clinical learning environments: a better and differentiated use of self-efficacy sources can stimulate the professional development of nursing students

Scanning Imaging Absorption Spectrometer for Atmospheric Chartography carbon monoxide total columns: Statistical evaluation and comparison with chemistry transport model results

This paper presents a detailed statistical analysis of one year (September 2003 to August 2004) of global Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) carbon monoxide (CO) total column retrievals from the Iterative Maximum Likelihood Method (IMLM) algorithm, version 6.3. SCIAMACHY provides the first solar reflectance measurements of CO and is uniquely sensitive down to the boundary layer. SCIAMACHY measurements and chemistry transport model (CTM) results are compared and jointly evaluated. Significant improvements in agreement occur, especially close to biomass burning emission regions, when the new Global Fire Emissions Database version 2 (GFEDv2) is used with the CTM. Globally, the seasonal variation of the model is very similar to that of the SCIAMACHY measurements. For certain locations, significant differences were found, which are likely related to modeling errors due to CO emission uncertainties. Statistical analysis shows that differences between single SCIAMACHY CO total column measurements and corresponding model results are primarily explained by random instrument noise errors. This strongly suggests that the random instrument noise errors are a good diagnostic for the precision of the measurements. The analysis also indicates that noise in single SCIAMACHY CO measurements is generally greater than actual variations in total columns. It is thus required to average SCIAMACHY data over larger temporal and spatial scales to obtain valuable information. Analyses of monthly averaged SCIAMACHY measurements over 3° × 2° geographical regions indicates that they are of sufficient accuracy to reveal valuable information about spatial and temporal variations in CO columns and provide an important tool for model validation. A large spatial and temporal variation in instrument noise errors exists which shows a close correspondence with the spatial distribution of surface albedo and cloud cover. This large spatial variability is important for the use of monthly and annual mean SCIAMACHY CO total column measurements. The smallest instrument noise errors of monthly mean 3° × 2° SCIAMACHY CO total columns measurements are 0.01 × 1018 molecules/cm2 for high surface albedo areas over the Sahara. Errors in SCIAMACHY CO total column retrievals due to errors other than instrument noise, like cloud cover, calibration, retrieval uncertainties and averaging kernels are estimated to be about 0.05–0.1 × 1018 molecules/cm2 in total. The bias found between model and observations is around 0.05–0.1 1018 molecules/cm2 (or about 5%) which also includes model errors. This thus provides a best estimate of the currently achievable measurement accuracy for SCIAMACHY CO monthly mean averages

Helping Made Easy: Ease of Argument Generation Enhances Intentions to Help

Previous work has shown that self-generating arguments is more persuasive than reading arguments provided by others, particularly if self-generation feels easy. The present study replicates and extends these findings by providing evidence for fluency effects on behavioral intention in the realm of helping. In two studies, participants were instructed to either self-generate or read two versus ten arguments about why it is good to help. Subsequently, a confederate asked them for help. Results show that self-generating few arguments is more effective than generating many arguments. While this pattern reverses for reading arguments, easy self-generation is the most effective strategy compared to all other conditions. These results have important implications for fostering behavioral change in all areas of life

The mucosal adjuvant cholera toxin B instructs non-mucosal dendritic cells to promote IgA production via retinoic acid and TGF-β

It is currently unknown how mucosal adjuvants cause induction of secretory immunoglobulin A (IgA), and how T cell-dependent (TD) or -independent (TI) pathways might be involved. Mucosal dendritic cells (DCs) are the primary antigen presenting cells driving TI IgA synthesis, by producing a proliferation-inducing ligand (APRIL), B cell activating factor (BAFF), Retinoic Acid (RA), TGF-beta or nitric oxide (NO). We hypothesized that the mucosal adjuvant Cholera Toxin subunit B (CTB) could imprint non-mucosal DCs to induce IgA synthesis, and studied the mechanism of its induction. In vitro, CTB-treated bone marrow derived DCs primed for IgA production by B cells without the help of T cells, yet required co-signaling by different Toll-like receptor (TLR) ligands acting via the MyD88 pathway. CTB-DC induced IgA production was blocked in vitro or in vivo when RA receptor antagonist, TGF-beta signaling inhibitor or neutralizing anti-TGF-beta was added, demonstrating the involvement of RA and TGF-beta in promoting IgA responses. There was no major involvement for BAFF, APRIL or NO. This study highlights that synergism between CTB and MyD88-dependent TLR signals selectively imprints a TI IgA-inducing capacity in non-mucosal DCs, explaining how CTB acts as an IgA promoting adjuvant

The evaluation of SCIAMACHY CO and CH_4 scientific data products, using ground-based FTIR measurements

In the framework of the European EVERGREEN project, three scientific algorithms, namely WFM-DOAS, IMAPDOAS and IMLM, have been developed to retrieve the total column amounts of key atmospheric trace gases including CO and CH_4 from SCIAMACHY nadir observations in its near-infrared channels. These channels offer the capability to detect trace gases in the planetary boundary layer, potentially making the associated retrieval products suited for regional source-sink studies. The retrieval products of these three algorithms, in their present status of development, have been compared to independent data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers, for the year 2003. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of coincidences that satisfy the temporal and spatial collocation criteria, the individual SCIAMACHY data points have been compared with a 3rd order polynomial interpolation of the ground-based data with time. Particular attention has been paid to the question whether the products reproduce correctly the seasonal and latitudinal variabilities of the target species. We present an overall assessment of the data quality of the currently available latest versions of the CO and CH4 total column products from the three scientific retrieval algorithms

No strong radio absorption detected in the low-frequency spectra of radio-loud quasars at z > 5.6

© 2023 The Author(s). Published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/We present the low-frequency radio spectra of 9 high-redshift quasars at $5.6 \leq z \leq 6.6$ using the Giant Metre Radio Telescope band-3, -4, and -5 observations ($\sim$300-1200 MHz), archival Low Frequency Array (LOFAR; 144 MHz), and Very Large Array (VLA; 1.4 and 3 GHz) data. Five of the quasars in our sample have been discovered recently, representing some of the highest redshift radio bright quasars known at low-frequencies. We model their radio spectra to study their radio emission mechanism and age of the radio jets by constraining the spectral turnover caused by synchrotron self-absorption (SSA) or free-free absorption (FFA). Besides J0309+2717, a blazar at $z=6.1$, our quasars show no sign of a spectral flattening between 144 MHz and a few GHz, indicating there is no strong SSA or FFA absorption in the observed frequency range. However, we find a wide range of spectral indices between $-1.6$ and $0.05$, including the discovery of 3 potential ultra-steep spectrum quasars. Using further archival VLBA data, we confirm that the radio SED of the blazar J0309+2717 likely turns over at a rest-frame frequency of 0.6-2.3 GHz (90-330 MHz observed frame), with a high-frequency break indicative of radiative ageing of the electron population in the radio lobes. Ultra-low frequency data below 50 MHz are necessary to constrain the absorption mechanism for J0309+2717 and the turnover frequencies for the other high-$z$ quasars in our sample. A relation between linear radio jet size and turnover frequency has been established at low redshifts. If this relation were to hold at high redshifts, the limits on the turnover frequency of our sample suggest the radio jet sizes must be more extended than the typical sizes observed in other radio-bright quasars at similar redshift. To confirm this deep radio follow-up observations with high spatial resolution are required.Peer reviewe

The impact of SCIAMACHY near-infrared instrument calibration on CH4 and CO total columns

The near-infrared spectra measured with the SCIAMACHY instrument on board the ENVISAT satellite suffer from several instrument calibration problems. The effects of three important instrument calibration issues on the retrieved methane (CH4) and carbon monoxide (CO) total columns have been investigated: the effects of the growing ice layer on the near-infrared detectors, the effects of the orbital variation of the instrument dark signal, and the effects of the dead/bad detector pixels. Corrections for each of these instrument calibration issues have been defined. The retrieved CH4 and CO total columns including these corrections show good agreement with CO measurements from the MOPITT satellite instrument and with CH4 model calculations by the chemistry transport model TM3. Using a systematic approach, it is shown that all three instrument calibration issues have a significant effect on the retrieved CH4 and CO total columns. However, the impact on the CH4 total columns is more pronounced than for CO, because of its smaller variability. Results for three different wavelength ranges are compared and show good agreement. The growing ice layer and the orbital variation of the dark signal show a systematic, but time-dependent effect on the retrieved CH4 and CO total columns, whereas the effect of the dead/bad pixels is rather unpredictable: some dead pixels show a random effect, some more systematic, and others no effect at all. The importance of accurate corrections for each of these instrument calibration issues is illustrated using examples where inaccurate corrections lead to a wrong interpretation of the results

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure