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This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, |GE | and |GM|, using the ¯pp → μ+μ− reaction at PANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at PANDA, using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is ¯pp → π+π−,due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distribuations of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented.
The physics goal of the strong interaction program of the NA61/SHINE experiment at the CERN Super Proton Synchrotron (SPS) is to study the phase diagram of hadronic matter by a scan of particle production in collisions of nuclei with various sizes at a set of energies covering the SPS energy range. This paper presents differential inclusive spectra of transverse momentum, transverse mass and rapidity of π− mesons produced in central 40Ar+45Sc collisions at beam momenta of 13A, 19A, 30A, 40A, 75A and 150A Ge V /c. Energy and system size dependence of parameters of these distributions – mean transverse mass, the inverse slope parameter of transverse mass spectra, width of the rapidity distribution and mean multiplicity – are presented and discussed. Furthermore, the dependence of the ratio of the mean number of produced pions to the mean number of wounded nucleons on the collision energy was derived. The results are compared to predictions of several models.
Plant community biomass production is co-dependent on climatic and edaphic factors that are often covarying and non-independent. Disentangling how these factors act in isolation is challenging, especially along large climatic gradients that can mask soil effects. As anthropogenic pressure increasingly alters local climate and soil resource supply unevenly across landscapes, our ability to predict concurrent changes in plant community processes requires clearer understandings of independent and interactive effects of climate and soil. To address this, we developed a multispecies phytometer (i.e., standardized plant community) for separating key drivers underlying plant productivity across gradients. Phytometers were composed of three globally cosmopolitan herbaceous perennials, Dactylis glomerata, Plantago lanceolata, and Trifolium pratense. In 2017, we grew phytometer communities in 18 sites across a pan-European aridity gradient in local site soils and a standardized substrate and compared biomass production. Standard substrate phytometers succeeded in providing a standardized climate biomass response independent of local soil effects. This allowed us to factor out climate effects in local soil phytometers, establishing that nitrogen availability did not predict biomass production, while phosphorus availability exerted a strong, positive effect independent of climate. Additionally, we identified a negative relationship between biomass production and potassium and magnesium availability. Species-specific biomass responses to the environment in the climate-corrected biomass were asynchronous, demonstrating the importance of species interactions in vegetation responses to global change. Biomass production was co-limited by climatic and soil drivers, with each species experiencing its own unique set of co-limitations. Our study demonstrates the potential of phytometers for disentangling effects of climate and soil on plant biomass production and suggests an increasing role of P limitation in the temperate regions of Europe.
Copper perchlorophthalocyanine (CuPcCl16, CuC32N8Cl16, Pigment Green 7) is one of the commercially most important green pigments. The compound is a nanocrystalline fully insoluble powder. Its crystal structure was first addressed by electron diffraction in 1972 [Uyeda et al. (1972). J. Appl. Phys. 43, 5181–5189]. Despite the commercial importance of the compound, the crystal structure remained undetermined until now. Using a special vacuum sublimation technique, micron-sized crystals could be obtained. Three-dimensional electron diffraction (3D ED) data were collected in two ways: (i) in static geometry using a combined stage-tilt/beam-tilt collection scheme and (ii) in continuous rotation mode. Both types of data allowed the crystal structure to be solved by direct methods. The structure was refined kinematically with anisotropic displacement parameters for all atoms. Due to the pronounced crystal mosaicity, a dynamic refinement was not feasible. The unit-cell parameters were verified by Rietveld refinement from powder X-ray diffraction data. The crystal structure was validated by many-body dispersion density functional theory (DFT) calculations. CuPcCl16 crystallizes in the space group C2/m (Z = 2), with the molecules arranged in layers. The structure agrees with that proposed in 1972.
Background: School attendance during the COVID-19 pandemic is intensely debated.
Aim: In November 2020, we assessed SARS-CoV-2 infections and seroreactivity in 24 randomly selected school classes and connected households in Berlin, Germany.
Methods: We collected oro-nasopharyngeal swabs and blood samples, examining SARS-CoV-2 infection and IgG antibodies by RT-PCR and ELISA. Household members self-swabbed. We assessed individual and institutional prevention measures. Classes with SARS-CoV-2 infection and connected households were retested after 1 week.
Results: We examined 1,119 participants, including 177 primary and 175 secondary school students, 142 staff and 625 household members. SARS-CoV-2 infection occurred in eight classes, affecting each 1–2 individuals. Infection prevalence was 2.7% (95% confidence interval (CI): 1.2–5.0; 9/338), 1.4% (95% CI: 0.2–5.1; 2/140), and 2.3% (95% CI: 1.3–3.8; 14/611) among students, staff and household members. Six of nine infected students were asymptomatic at testing. We detected IgG antibodies in 2.0% (95%CI: 0.8–4.1; 7/347), 1.4% (95% CI: 0.2–5.0; 2/141) and 1.4% (95% CI: 0.6–2.7; 8/576). Prevalence increased with inconsistent facemask-use in school, walking to school, and case-contacts outside school. For three of nine households with infection(s), origin in school seemed possible. After 1 week, no school-related secondary infections appeared in affected classes; the attack rate in connected households was 1.1%.
Conclusion: School attendance under rigorously implemented preventive measures seems reasonable. Balancing risks and benefits of school closures need to consider possible spill-over infection into households. Deeper insight is required into the infection risks due to being a schoolchild vs attending school.
Background: School attendance during the SARS-CoV-2 pandemic is intensely debated. Modelling studies suggest that school closures contribute to community transmission reduction. However, data among school-attending students and staff are scarce. In November 2020, we examined SARS-CoV-2 infections and seroreactivity in 24 randomly selected school classes and connected households in Berlin, Germany.
Methods: Students and school staff were examined, oro-nasopharyngeal swabs and blood samples collected, and SARS-CoV-2 infection and IgG antibodies detected by RT-PCR and ELISA. Household members performed self-swabs. Individual and institutional infection prevention and control measures were assessed. Classes with SARS-CoV-2 infection and connected household members were re-tested after one week.
Findings: 1119 participants were examined, including 177 primary and 175 secondary school students, 142 staff, and 625 household members. Participants reported mainly cold symptoms (19·4%). SARS-CoV-2 infection occurred in eight of 24 classes affecting each 1-2 individuals. Infection prevalence was 2·7% (95%CI; 1·2-5·0%; 9/338), 1·4% (0·2-5·1%; 2/140), and 2·3% (1·3-3·8%; 14/611) among students, staff and household members, respectively, including quarantined persons. Six of nine infected students were asymptomatic. Prevalence increased with inconsistent facemask use in school, way to school on foot, and case-contacts outside school. IgG antibodies were detected in 2·0% (0·8-4·1%; 7/347), 1·4% (0·2-5·0%; 2/141) and 1·4% (0·6-2·7%; 8/576), respectively. For three of nine households with infection(s) detected at cross-sectional assessment, origin in school seemed possible. After one week, no school-related, secondary infections appeared in affected classes; the attack rate in connected households was 1·1%.
Interpretation: These data suggest that school attendance under preventive measures is feasible, provided their rigorous implementation. In balancing threats and benefits of open versus closed schools during the pandemic, parents and society need to consider possible spill-overs into their households. Deeper insight is needed into the infection risks due to being a schoolchild as compared to attending school.