Measuring the value of a digital supplemental resource

Supplemental resources in science education are made available to students based on the belief that they will improve course-based student learning. This belief is ubiquitous, with supplemental resources being a traditional component of physiology education. In addition, the recent large-scale transition to remote learning caused by the Covid-19 pandemic suggests an increased relevance and necessity of digital versions of supplemental resources. However, the use of a supplemental resource is entirely dependent on whether students view it as beneficial. If students in a specific course do not perceive a supplemental resource as useful, there is little reason to believe the resources will be used and are worthy of investment. Consequently, measurement of student perception regarding the effectiveness of any digital learning tool is essential for educators and institutions in order to prioritize resources and make meaningful recommendations to students. In this study, a survey was used to determine student perceptions of a digital, supplemental resource. Quantitative methods, including exploratory factor analysis, were performed on data collected from the survey to examine the dimensionality and functionality of this survey. The findings from this study were used to devise an improved, standardized (i.e., reliable and valid) survey that can be used and adapted by physi3ology researchers and educators to determine student perception of a digital supplemental resource. The survey, with known construct validity and internal reliability, can provide useful information for administrators, instructors, and designers of digital supplemental resources.

Flooding Fragility Model Development Using Bayesian Regression

Traditional component pass/fail design analysis and testing protocol drives excessively conservative operating limits and setpoints as well as unnecessarily large margins of safety. Component performance testing coupled with failure probability model development can support selection of more flexible operating limits and setpoints as well as softening defense-in-depth elements. This chapter discuses the process of Bayesian regression fragility model development using Markov Chain Monte Carlo methods and model checking protocol using three types of Bayesian p-values. The chapter also discusses application of the model development and testing techniques through component flooding performance experiments associated with industrial steel doors being subjected to a rising water scenario. These component tests yield the necessary data for fragility model development while providing insight into development of testing protocol that will yield meaningful data for fragility model development. Finally, the chapter discusses development and selection of a fragility model for industrial steel door performance when subjected to a water-rising scenario.

Stellar angular momentum distribution linked to galaxy morphology

ABSTRACT We study the spatially resolved stellar specific angular momentum j* in a high-quality sample of 24 Calar Alto Legacy Integral Field Area galaxies covering a broad range of visual morphology, accounting for stellar velocity and velocity dispersion. The shape of the spaxelwise probability density function of normalized s = j*/j*mean, PDF(s), deviates significantly from the near-universal initial distribution expected of baryons in a dark matter halo and can be explained by the expected baryonic effects in galaxy formation that remove and redistribute angular momentum. Further we find that the observed shape of the PDF(s) correlates significantly with photometric morphology, where late-type galaxies have a PDF(s) that is similar to a normal distribution, whereas early types have a strongly skewed PDF(s) resulting from an excess of low-angular momentum material. Galaxies that are known to host pseudo-bulges (bulge Sérsic index nb < 2.2) tend to have less skewed bulge PDF(s), with skewness (b1rb) ≲ 0.8. The PDF(s) encodes both kinematic and photometric information and appears to be a robust tracer of morphology. Its use is motivated by the desire to move away from traditional component-based classifications which are subject to observer bias, to classification on a galaxy’s fundamental (stellar mass and angular momentum) properties. In future, PDF(s) may also be useful as a kinematic decomposition tool.

Animal Transformation in Early Modern English Witchcraft Pamphlets

Animal metamorphosis was a traditional component of witchcraft beliefs during the European early modern witch-hunts, during which it was taken for granted that witches could and did turn into animals regularly in order to easier do evil. It must be noted, however, that the witch-turned-animal motif was much less common in England, where witches did possess the shape-shifting abilities but relatively rarely used them. A likely reason for the difference, explored in the present paper, was the specifically English belief that most witches were accompanied and served by familiar spirits, petty demons that customarily assumed the shape of animals. It seems that the ubiquity of such demonic shape-shifters effectively satisfied the demand for magical transformations in the English witchcraft lore.

A Method for Evaluating Manufacturing Change in Engineering Design

This paper details a method of change prediction that builds upon the traditional component-component design structure matrix by incorporating manufacturing costs and modeling higher orders of coupling. A coupling index is also created to assess the level of coupling between interfaced features. A BMW X5 headliner assembly and a Ryobi hand-held drill are analyzed using the proposed method to identify the features and components that offer the greatest ease of change. The analysis of the BMW X5 headliner shows that the rectangular slots on the bottom of the adapter plates are the feature that offers the greatest ease of change, while the handles are the component that offers the greatest ease of change. For the Ryobi drill, the battery is identified as the component that offers the greatest ease of change. The proposed method of change prediction proves to be an effective and efficient means of modeling change propagation and assessing change impact.