University of Mount Union

Introductory classes are often a student’s first exposure to foundational knowledge, careers, and faculty in an academic major. The characteristics of introductory exercise science courses, as well as faculty impressions of course benefits and areas for improvement, were explored in this study. Electronic survey data from 181 universities around the United States were analyzed. A wide range of course content was reported. Institution type was related to the status of the faculty teaching the course, method of course delivery, class size, and class availability. The number of majors was related to faculty status, class availability, and class size. Specifically, private 4-year institutions were more likely to teach smaller, face-to-face classes. Introduction courses at R1, R2, Doctoral/Professional institutions, and programs with 300 or more majors were less likely to be taught by only tenured/tenure track faculty. Classes were more likely to be offered in various modalities as opposed to only face-to-face at community colleges, and programs with 300 or more majors were more likely to have classes with 50 or more students. Enrollment in the introductory course was more likely restricted to majors and minors at public 4-year schools and programs with 300 or more majors. Faculty perceived knowledge acquisition and relationship building as benefits of introductory classes for students and programs. The overarching themes for course improvement were modifying course content and characteristics of course delivery. Considering the varied course characteristics, we encourage faculty and administrators to be intentional when designing and implementing introductory exercise science courses.

This chapter looks at Donald Trump as the benefactor of the realignment of American politics that began with Ronald Reagan and discusses his use of populist rhetoric to not only garner support from a large segment of the population that saw itself as disenfranchised, but to transform American political discourse. In introducing the remaining chapters, the chapter identifies the major impacts Trump had on the United States and the world, noting that, in many ways, he was not very transformative. Rather, many of his policies were traditional Republican policies. Where he did differ was in his rhetoric and his ability to give voice to those who saw themselves as disenfranchised.

This chapter summarizes and synthesizes the chapters in the book. The chapter argues that while Trump’s domestic policies did not differ greatly from other Republican presidents, his foreign policy did represent a break from his predecessors, alienating many traditional allies and presenting a direct challenge to America’s post-Cold War leadership position. Most importantly, this chapter focuses on Trump’s rhetorical style and his willingness to lean into a nationalist-populist message, noting that this may be where his greatest legacy may lie.

In this chapter, we examine larger systems of oppression encapsulating all aspects of life including engineering practice and education. We describe a direction for engineering education with the goal of building a socially just and peaceful society. The particular focus is on ‘transitions’ from ‘business-as-usual’ to equitable societies living within the planetary limits, termed ‘just’ by multiple intersectional grassroots social movements. We uncover the underlying assumptions in current engineering practice and associated education building on ideas expressed in Chap. 1 and demonstrate how engaging with social movements in the realm of engineering education provides a pathway towards creating a just and peaceful world.

The homogeneous electron gas is a system that has many applications in chemistry and physics. However, its infinite nature makes studies at the many-body level complicated due to long computational run times. Because it is size extensive, coupled cluster theory is capable of studying the homogeneous electron gas, but it still poses a large computational challenge as the time needed for precise calculations increases in a polynomial manner with the number of particles and single-particle states. Consequently, achieving convergence in energy calculations becomes challenging, if not prohibited, due to long computational run times and high computational resource requirements. This paper develops the sequential regression extrapolation (SRE) to predict the coupled cluster energies of the homogeneous electron gas in the complete basis limit using Bayesian ridge regression and many-body perturbation theory correlation energies to the second order to make predictions from calculations at truncated basis sizes. Using the SRE method, we were able to predict the coupled cluster double energies for the electron gas across a variety of values of N and rs, for a total of 70 predictions, with an average error of 5.20 × 10⁻⁴ hartree while saving 88.9 h of computational time. The SRE method can accurately extrapolate electron gas energies to the complete basis limit, saving both computational time and resources. Additionally, the SRE is a general method that can be applied to a variety of systems, many-body methods, and extrapolations.

Teaching health professions at the graduate level often involves instructors guiding students through active learning labs for the practical application of content. Clinical courses may necessitate covering a substantial amount of information, requiring instructors to adopt efficient and effective teaching methods to maximize lab time. In a Master of Occupational Therapy Program, students were observed being off-task and disengaged with provided materials during group work in active learning labs. In response to this, Quick Response (QR) codes were introduced as a strategy to enhance self-directed learning and maintain focus on tasks while the instructor offered supplemental assistance as needed. A Microsoft Form survey was administered after classes to assess the effectiveness of QR codes as a technology-supported instructional method and gather students’ perceptions. The survey results overwhelmingly indicated that students were receptive to using QR codes and found them helpful in facilitating learning and maintaining attention during lab activities.

Background Most stroke survivors consider community ambulation an essential but unmet goal of their recovery. Historically, interventions to enhance community ambulation have focused on improving biomechanical impairments of gait; however, recent evidence suggests that biopsychosocial and environmental factors may impact community ambulation, even beyond more obvious physical impairments. The identification of factors that pose as significant facilitators or barriers to community ambulation may serve to guide stakeholders in designing relevant and evidence-based interventions for improving community ambulation post-stroke. Objective This review aims to map the type and extent of existing evidence on the physical, biopsychosocial, and environmental factors affecting community ambulation post-stroke. Additionally, this review will describe the various methods used to examine the extent to which stroke survivors are restricted to community ambulation. Methods Nine databases will be searched including CINAHL, PubMed, and Web of Science. We will include studies published in English during or after 2001. Studies that examine physical, biopsychosocial, and/or environmental factors affecting community ambulation in ambulatory adults at least six months post-stroke will be considered for inclusion. Studies that assess general physical activity or community mobility through transportation modes other than walking will be excluded. All identified records will be collated in citation management software, followed by steps of deduplication, title/abstract screening, and full-text reviews by at least two independent reviewers. The bibliographies of the extracted studies will also be reviewed for relevant articles. The extracted studies will be analyzed, critically appraised, and presented in tabular, narrative, and evidence map formats. Discussion The evidence gained will be used to build a framework for community ambulation, informing stakeholders to develop meaningful interventions to improve community ambulation. The mapped evidence will motivate future studies to develop holistic approaches that specifically focus on the most vital factors that influence post-stroke community ambulation.

Aim The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location Conterminous United States. Time Period 2010–2021. Major Taxa Studied Twenty‐five species of mammals. Methods We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard‐mast tree species. The mammal community maps are similar to those of plants, with an east–west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine‐scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Needle pathogens cause the discoloration, death, or premature abscission of conifer foliage, reducing growth and vigor, and repeated defoliation may eventually result in tree mortality. Since 2016, forest managers in the southeast United States have reported an increasing scale, frequency, and severity of needle disease outbreaks on the region’s principal timber species, loblolly pine (Pinus taeda L.). These recent outbreaks are raising concern throughout the region, as needle diseases are not traditionally considered a threat to P. taeda. Lecanosticta acicola (Thum.) Syd., the native causal agent of brown-spot needle blight, has been recovered from some outbreaks, however, the full array of fungi associated with symptoms has not been explored. In this research, P. taeda foliage was collected from affected stands throughout the region and analyzed to identify fungi associated with needle disease symptoms. We employed targeted molecular diagnostics, to confirm the presence or absence of L. acicola, and DNA metabarcoding, to characterize the foliar mycobiome and screen for other potential pathogens. Lecanosticta acicola was detected among symptomatic needles from multiple states, particularly in western portions of the P. taeda range but rarely from stands in eastern states. Metabarcoding revealed pathogens in needles and identified associations among pathogenic fungi, differing symptoms, including needle discoloration and necrosis, and signs of fungal fruiting bodies. Additionally, the fungal community of needles varied with patterns of symptom presentation. This study is the first regionwide assessment of fungi associated with recent large-scale needle disease outbreaks on P. taeda and identifies multiple pathogens that warrant further study.

Background: Gait speed or 6-minute walk test are frequently used to project community ambulation abilities post-stroke by categorizing individuals as household ambulators, limited, or unlimited community ambulators. However, whether improved clinically-assessed gait outcomes truly translate into enhanced real-world community ambulation remains uncertain. Objective This cross-sectional study aimed to examine differences in home and community ambulation between established categories of speed- and endurance-based classification systems of community ambulation post-stroke and compare these with healthy controls. Methods: Sixty stroke survivors and 18 healthy controls participated. Stroke survivors were categorized into low-speed, medium-speed, or high-speed groups based on speed-based classifications and into low-endurance, medium-endurance, or high-endurance groups based on the endurance-based classification. Home and community steps/day were quantified using Global Positioning System and accelerometer devices over 7 days. Results: The low-speed groups exhibited fewer home and community steps/day than their medium- and high-speed counterparts (P < .05). The low-endurance group took fewer community steps/day than the high-endurance group (P < .05). Despite vast differences in clinical measures of gait speed and endurance, the medium-speed/endurance groups did not differ in their home and community steps/day from the high-speed/endurance groups, respectively. Stroke survivors took 48% fewer home steps/day and 77% fewer community steps/day than healthy controls. Conclusions: Clinical classification systems may only distinguish home ambulators from community ambulators, but not between levels of community ambulation, especially beyond certain thresholds of gait speed and endurance. Clinicians should use caution when predicting community ambulation status through clinical measures, due to the limited translation of these classification systems into the real world.