Virginia Wesleyan College

This manuscript emphasizes the role of debate in promoting individual competencies necessary for democratic engagement. By simulating actual democratic processes, our debate course provided students with practical experience in deliberation and perspective-taking. This approach encourages students to navigate complex societal issues, fostering an appreciation of the nuances of argumentation while cultivating empathy towards differing viewpoints. These findings suggest that structured debates can serve as a tool for promoting democratic skills among college students, preparing them to become informed, active participants in their political communities.

Previous work has examined the relations between feminism, feminine gender roles, and body image concerns with inconclusive findings. The purpose of this study was to conduct an updated meta-analysis of the relation between feminist identity and negative embodiment, and to conduct new analyses to test how endorsement of femininity relates to negative embodiment. Through the technique of meta-analysis, we analyzed 80 studies (87 samples, N = 24,308) and 217 effect sizes to examine these associations. The predictor variables were measures of feminist identity and endorsement of femininity. The negative embodiment criterion variables were measures of body dissatisfaction, self-objectification, internalization of cultural body ideals, and disordered eating attitudes. Feminist identity was found to be negatively associated with negative embodiment, but only modestly, with small but significant effect sizes across most variables. Endorsement of femininity was found to be positively associated with negative embodiment, with mostly significant effect sizes ranging from small to large. These findings underscore the importance of considering the roles of feminist identity and traditional gender ideology in the etiology and prevention of women’s experiences of negative embodiment.

Fentanyl (FTN) and synthetic analogs of FTN continue to ravage populations across the globe, including in the United States where opioids are increasingly being used and abused and are causing a staggering and growing number of overdose deaths each year. This growing pandemic is worsened by the ease with which FTN can be derivatized into numerous derivatives. Understanding the chemical properties/behaviors of the FTN class of compounds is critical for developing effective chemical detection schemes using nanoparticles (NPs) to optimize important chemical interactions. Halogen bonding (XB) is an intermolecular interaction between a polarized halogen atom on a molecule and e⁻-rich sites on another molecule, the latter of which is present at two or more sites on most fentanyl-type structures. Density functional theory (DFT) is used to identify these XB acceptor sites on different FTN derivatives. The high toxicity of these compounds necessitated a “fragmentation” strategy where smaller, non-toxic molecules resembling parts of the opioids acted as mimics of XB acceptor sites present on intact FTN and its derivatives. DFT of the fragments’ interactions informed solution measurements of XB using ¹⁹F NMR titrations as well as electrochemical measurements of XB at self-assembled monolayer (SAM)-modified electrodes featuring XB donor ligands. Gold NPs, known as monolayer-protected clusters (MPCs), were also functionalized with strong XB donor ligands and assembled into films, and their interactions with FTN “fragments” were studied using voltammetry. Ultimately, spectroscopy and TEM analysis were combined to study whole-molecule FTN interactions with the functionalized MPCs in solution. The results suggested that the strongest XB interaction site on FTN, while common to most of the drug’s derivatives, is not strong enough to induce NP-aggregation detection but may be better exploited in sensing schemes involving films.

Deep learning models, particularly Convolutional Neural Networks (CNNs), play a pivotal role in intelligent software. However, like any software application, CNN-based applications are susceptible to bugs. Bug-fix patterns in CNN differ from traditional techniques, primarily due to their inherent black-box nature. Moreover, current methods, although tailored for generic DNN structures, are time consuming, require specialized expertise, and are not directly applicable to the unique structure and requirements of CNNs. To address these issues, we propose DeepCNN, an innovative automated tool to identify the root causes of CNN faults and autonomously fix prevalent training faults that impact the performance and efficiency of CNN programs. DeepCNN, a data-driven tool, employs a transformer encoder model to abstract token-level CNN code, enabling it to effectively detect and fix bugs in real-world CNN models. Beyond mere identification, DeepCNN offers automated solutions for repairing CNN hyperparameter misconfigurations using an optimization solver. Additionally, by analyzing data dependencies and employing a search algorithm, it determines the most optimal hyperparameter values for the problematic models, ultimately generating patch fixes. Through rigorous evaluation on 36 diverse buggy models, DeepCNN outperformed existing methods in fault localization and repair, showing a robustness in identifying potential problems with a 90% detection rate. Among these problematic models, it manages to repair 90% of them — resulting in a 30% average accuracy boost.

Seedless plants utilize flagellated sperm cells for reproduction that develop using a series of cell walls resulting in naked motile cells. Arabinogalactan Proteins (AGPs) have been shown to play an important role in the maturation of sperm in ferns by an unknown mechanism. We sought to identify AGPs expressed in the spermatids of the moss Physcomitrium patens to identify this mechanism because it is amenable to genetic manipulation. We tracked the expression of 121 putative AGP-encoding genes across three time points of development with RNAseq and quantified total AGPs to compare to the fern Ceratopteris richardii. Unexpectedly, AGP genes and proteins were significantly downregulated in P. patens. BURP domain-containing genes, which are expressed in pollen of angiosperms, were highly upregulated and may serve similar roles to the AGPs of ferns. This study shows that the fern cell walls do not share as significant of a need for AGPs of developing sperm in bryophytes and this may be related to the number of flagella found in the respective lineages.

The purpose of the current study is to explore several correlates of adolescent students’ preferences for at-home virtual or in-class in-person learning in a single case of a school that serves students with learning differences. Correlates of interest were the Big Five personality traits (Openness to Experience, Conscientiousness, Extroversion, Agreeableness, Neuroticism) and the students’ self-reported learning engagement. Participants were recruited from a single independent school for students with neurodiversity and special learning needs, where they had high exposure to computer-/internet-assisted learning. Twenty-seven students responded to questionnaires measuring preferred learning modes, personality traits, and learning engagement. Despite teacher reports that some of these students thrived with virtual learning during the COVID-19 pandemic, 88.5% of this sample preferred in-class learning. The personality traits of Conscientiousness and Openness to Experience were related to a preference for in-class learning. A preference for in-class learning was related, in turn, to learning engagement. Learning engagement was associated with Conscientiousness, Agreeableness, and lower levels of Neuroticism. The strengths and limitations of this study and its implications for further research and practice are discussed.

Retrieval practice can reduce associative memory deficits for older adults but they underutilize this potent learning tool during self-regulated learning. The current experiment investigated whether teaching older adults to use retrieval practice more can improve their self-regulated learning. Younger and older adults made decisions about when to study, how often to engage in retrieval practice, and when to stop learning a list of medication-side effect pairs. Some younger and older adults received instructions before learning that emphasized the mnemonic benefits of retrieval practice over restudying material and described how to schedule retrieval practice to learn to a goal criterion level. This minimal intervention was effective for improving both younger and older adults' associative memory. These data indicate that a simple strategy for improving older adults self-regulated learning is to provide them with instructions that teach them how to use criterion learning to schedule their retrieval practice for to-be learned material.

The Body Appreciation Scale-2 (BAS-2) is a widely used measure of a core facet of the positive body image construct. However, extant research concerning measurement invariance of the BAS-2 across a large number of nations remains limited. Here, we utilised the Body Image in Nature (BINS) dataset – with data collected between 2020 and 2022 – to assess measurement invariance of the BAS-2 across 65 nations, 40 languages, gender identities, and age groups. Multi-group confirmatory factor analysis indicated that full scalar invariance was upheld across all nations, languages, gender identities, and age groups, suggesting that the unidimensional BAS-2 model has widespread applicability. There were large differences across nations and languages in latent body appreciation, while differences across gender identities and age groups were negligible-to-small. Additionally, greater body appreciation was significantly associated with higher life satisfaction, being single (versus being married or in a committed relationship), and greater rurality (versus urbanicity). Across a subset of nations where nation-level data were available, greater body appreciation was also significantly associated with greater cultural distance from the United States and greater relative income inequality. These findings suggest that the BAS-2 likely captures a near-universal conceptualisation of the body appreciation construct, which should facilitate further cross-cultural research.

Harvestmen exhibit substantial responses to environmental conditions, disturbances, and modifications of their habitat. We examined the abundance and species distribution of harvestmen along an elevational gradient in the Luquillo Experimental Forest (LEF) on Puerto Rico 6–12 weeks before and 9–10 months after Hurricane Maria passed over the island in September, 2017. This provided a unique opportunity to examine the effects of a major storm on litter-dwelling arthropod populations, as the storm led to a much greater abundance of leaf litter and downed branches. The abundance of harvestmen was measured in quadrat samples from 300 to 1,000 m elevation using Winkler samplers. We observed greater harvestmen abundance post-storm, which was similar to the results for most other arthropod groups. Pre-storm, harvestmen showed greater abundance in palm habitat, as compared to forests that were a mix of broadleaf and palm vegetation. Across all sampling periods, harvestmen were most abundant at low to medium elevations (300–600 m), especially for the two dominant taxa (Stygnomma spinula and Metacynortoides obscura obscura). Our findings are similar to results obtained from manipulative studies in the LEF several years prior to the hurricane. A challenge for the future is to understand the ways that the projected increase in storm severity due to climate change can affect various invertebrate groups such as harvestmen, and how tropical forests can remain resilient to such disturbances.