Guidance in the chaos:Effects of science communication by virologists during the COVID-19 crisis in Germany and the role of parasocial phenomena

During the COVID-19 pandemic, virologists gained a prominent role in traditional and social media in Germany; several participated in regular podcasts. Using a two-wave survey (n = 696/361 at Time 1/2), we explore which impact the strong media presence of virologists had on media users and what role parasocial phenomena (asymmetric interactions and relationships with virologists) played. People who favored a specific virologist scored higher on various cognitive, affective, and behavioral outcomes. Exposure to the virologist was related to these outcomes and parasocial phenomena turned out as an intervening variable between exposure and subjective and objective knowledge (time 1), solace, and behavioral engagement (both times). We did not, however, find effects over time when controlling for the time 1 values, which rather speak against more long-term media effects. A higher need for leadership also predicted the formation of parasocial phenomena. We discuss the theoretical implications for the role of parasocial phenomena in science communication via digital media

Y3_{3}Al5_{5}O12_{12}: Ce nanoparticles made by ionic-liquid-assisted particle formation and LiCl-matrix-treated crystallization

Y3Al5O12:Ce3+ (YAG:Ce) nanoparticles were prepared by a two-step approach including ionic-liquid-assisted particle formation and LiCl-matrix-treated crystallization. Subsequent to particle formation in [MeBu3N][N(SO2CF3)2] as the ionic liquid (MeBu3N: tributylmethylammonium; N(SO2CF3)2: bis(trifluoromethanesulfonyl)imide), the as-obtained amorphous precursor nanoparticles were crystallized in a LiCl matrix (600 °C, 1 h). The resulting YAG:Ce nanoparticles are well crystallized and exhibit a diameter of about 40 nm. They show bulk-like luminescence and a quantum yield of 51(±3)%. The selected Y : Al ratio and temperature profile turned out to be optimal for the synthesis strategy in terms of particle size and luminescence properties although minor amounts of CeO2 remained. The YAG:Ce nanoparticles can be easily redispersed in the liquid phase and embedded in polymers such as polyester. The course of the reaction and the properties of the nanoparticles are characterized by electron microscopy, dynamic light scattering, infrared spectroscopy, X-ray powder diffraction, and fluorescence spectroscopy

Ionic-liquid-based synthesis of GaN nanoparticles

GaN nanoparticles, 3–8 nm in diameter, are prepared by a microwave-assisted reaction of GaCl3 and KNH2 in ionic liquids. Instantaneously after the liquid-phase synthesis, the β-GaN nanoparticles are single-crystalline. The band gap is blue-shifted by 0.6 eV in comparison to bulk-GaN indicating quantum confinement effects. The GaN nanoparticles show intense green emission with a quantum yield of 55 ± 3%

Controls on Ecosystem Carbon Dioxide Exchange in Short- and Long-Hydroperiod Florida Everglades Freshwater Marshes

Although freshwater wetlands are among the most productive ecosystems on Earth, little is known of carbon dioxide (CO2) exchange in low latitude wetlands. The Everglades is an extensive, oligotrophic wetland in south Florida characterized by short- and long-hydroperiod marshes. Chamber-based CO2 exchange measurements were made to compare the marshes and examine the roles of primary producers, seasonality, and environmental drivers in determining exchange rates. Low rates of CO2 exchange were observed in both marshes with net ecosystem production reaching maxima of 3.77 and 4.28 μmol CO2 m−2 s−1 in short- and long-hydroperiod marshes, respectively. Fluxes of CO2 were affected by seasonality only in the short-hydroperiod marsh, where flux rates were significantly lower in the wet season than in the dry season. Emergent macrophytes dominated fluxes at both sites, though this was not the case for the short-hydroperiod marsh in the wet season. Water depth, a factor partly under human control, significantly affected gross ecosystem production at the short-hydroperiod marsh. As Everglades ecosystem restoration proceeds, leading to deeper water and longer hydroperiods, productivity in short-hydroperiod marshes will likely be more negatively affected than in long-hydroperiod marshes. The Everglades stand in contrast to many freshwater wetlands because of ecosystem-wide low productivity rates

Assessing exposure, uptake and toxicity of silver and cerium dioxide nanoparticles from contaminated environments

The aim of this project was to compare cerium oxide and silver particles of different sizes for their potential for uptake by aquatic species, human exposure via ingestion of contaminated food sources and to assess their resultant toxicity. The results demonstrate the potential for uptake of nano and larger particles by fish via the gastrointestinal tract, and by human intestinal epithelial cells, therefore suggesting that ingestion is a viable route of uptake into different organism types. A consistency was also shown in the sensitivity of aquatic, fish cell and human cell models to Ag and CeO2 particles of different sizes; with the observed sensitivity sequence from highest to lowest as: nano-Ag > micro Ag > nano CeO2 = micro CeO2. Such consistency suggests that further studies might allow extrapolation of results between different models and species

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6–17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.</p

Winter wheat yield prediction using convolutional neural networks from environmental and phenological data

Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning and deep learning methods for winter wheat yield prediction using an extensive dataset of weather, soil, and crop phenology variables in 271 counties across Germany from 1999 to 2019. We proposed a Convolutional Neural Network (CNN) model, which uses a 1-dimensional convolution operation to capture the time dependencies of environmental variables. We used eight supervised machine learning models as baselines and evaluated their predictive performance using RMSE, MAE, and correlation coefficient metrics to benchmark the yield prediction results. Our findings suggested that nonlinear models such as the proposed CNN, Deep Neural Network (DNN), and XGBoost were more effective in understanding the relationship between the crop yield and input data compared to the linear models. Our proposed CNN model outperformed all other baseline models used for winter wheat yield prediction (7 to 14% lower RMSE, 3 to 15% lower MAE, and 4 to 50% higher correlation coefficient than the best performing baseline across test data). We aggregated soil moisture and meteorological features at the weekly resolution to address the seasonality of the data. We also moved beyond prediction and interpreted the outputs of our proposed CNN model using SHAP and force plots which provided key insights in explaining the yield prediction results (importance of variables by time). We found DUL, wind speed at week ten, and radiation amount at week seven as the most critical features in winter wheat yield prediction

Researching interactions between humans and machines: methodological challenges

Communication scholars are increasingly concerned with interactions between humans and communicative agents. These agents, however, are considerably different from digital or social media: They are designed and perceived as life-like communication partners (i.e., as “communicative subjects”), which in turn poses distinct challenges for their empirical study. Hence, in this paper, we document, discuss, and evaluate potentials and pitfalls that typically arise for communication scholars when investigating simulated or non-simulated interactions between humans and chatbots, voice assistants, or social robots. In this paper, we focus on experiments (including pre-recorded stimuli, vignettes and the “Wizard of Oz”-technique) and field studies. Overall, this paper aims to provide guidance and support for communication scholars who want to empirically study human-machine communication. To this end, we not only compile potential challenges, but also recommend specific strategies and approaches. In addition, our reflections on current methodological challenges serve as a starting point for discussions in communication science on how meaning-making between humans and machines can be investigated in the best way possible, as illustrated in the concluding section

Measurement of J/Psi production in pp collisions at sqrt(s)=2.76 and 7 TeV with ALICE

We present results from the ALICE experiment on the inclusive J/Psi production in pp collisions at sqrt(s)=2.76 and 7 TeV. The integrated and differential cross sections are evaluated down to pT=0 in two rapidity ranges, |y|<0.9 and 2.5<y<4, in the dielectron and dimuon decay channel respectively. The measurement at sqrt(s)=2.76 TeV, the same energy as Pb-Pb collisions, provides a crucial reference for the study of hot nuclear matter effects on J/Psi production. The J/Psi yield in pp collisions at sqrt(s)=7 TeV has also been studied as a function of the charged particle multiplicity and first results are presented.Comment: 4 pages, 4 figures, parallel talk at Quark Matter 2011, Annecy, Franc

Clinical and functional characterisation of the combined respiratory chain defect in two sisters due to autosomal recessive mutations in MTFMT.

Exome sequencing identified compound heterozygous mutations in the recently discovered mitochondrial methionyl-tRNA formyltransferase (MTFMT) gene in two sisters with mild Leigh syndrome and combined respiratory chain deficiency. The mutations lead to undetectable levels of the MTFMT protein. Blue native polyacrylamide gel electrophoresis showed decreased complexes I and IV, and additional products stained with complex V antibodies, however the overall steady state level of mt-tRNA(Met) was normal. Our data illustrate that exome sequencing is an excellent diagnostic tool, and its value in clinical medicine is enormous, however it can only be optimally exploited if combined with detailed phenotyping and functional studies