CO diffusion into amorphous H2O ices

The mobility of atoms, molecules, and radicals in icy grain mantles regulates ice restructuring, desorption, and chemistry in astrophysical environments. Interstellar ices are dominated by H2O, and diffusion on external and internal (pore) surfaces of H2O-rich ices is therefore a key process to constrain. This study aims to quantify the diffusion kinetics and barrier of the abundant ice constituent CO into H2O-dominated ices at low temperatures (15–23 K), by measuring the mixing rate of initially layered H2O(:CO2)/CO ices. The mixed fraction of CO as a function of time is determined by monitoring the shape of the infrared CO stretching band. Mixing is observed at all investigated temperatures on minute timescales and can be ascribed to CO diffusion in H2O ice pores. The diffusion coefficient and final mixed fraction depend on ice temperature, porosity, thickness, and composition. The experiments are analyzed by applying Fick's diffusion equation under the assumption that mixing is due to CO diffusion into an immobile H2O ice. The extracted energy barrier for CO diffusion into amorphous H2O ice is ~160 K. This is effectively a surface diffusion barrier. The derived barrier is low compared to current surface diffusion barriers in use in astrochemical models. Its adoption may significantly change the expected timescales for different ice processes in interstellar environments.Astronom

Assessing Student Mindset, Interest, Participation, and Rapport in the Post-Pandemic Public Speaking Classroom: Effects of Modality Change and Communication Growth Mindset

The COVID-19 pandemic created an exigency for educators to reevaluate their approaches to the classroom with one major dimension being course modality. This study uses the Instructional Beliefs Model to examine the impacts of course modality (i.e., hybrid versus face-to-face formats) and students’ communication growth mindset on student engagement in the foundational public speaking course. Consistent with pre-COVID-19 findings, the results indicated that modality does not significantly impact student engagement, with one exception: higher cognitive interest scores were reported among students in the hybrid modality. Communication growth mindset associated positively with all student engagement variables examined: student interest–emotional, student interest–cognitive, participation, and class rapport. The findings offer tentative optimism about the promise of blended public speaking course modalities, and evidence for the necessity of mindset intervention to maximize student success

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future