Ball State University

SUMMARYThe goal of the Molecular Transducers of Physical Activity Consortium (MoTrPAC) is to examine the physiological and molecular basis for health benefits in response to acute and chronic exercise. Prior to COVID-19 suspension, healthy, sedentary participants (N=206, 18-74y) were randomized to endurance exercise (N=80), resistance exercise (N=81), or non-exercise control (N=45) interventions. The prescribed vigorous acute endurance and resistance exercise bouts induced physiological and metabolic perturbations relative to resting homeostasis. The supervised chronic (3d/wk, 12wk) endurance or resistance training programs robustly improved several physiological parameters (i.e., VO2peak, muscular strength). Temporal biospecimen (blood, muscle, and adipose) collections and processing coupled to the acute exercise bouts were highly successful. In most cases, over 90% success was achieved for blood, muscle, and adipose samples. Endurance and resistance exercise induced distinct acute and chronic physiological responses, which provide a framework to interrogate the molecular basis for health adaptations to these two popular exercise modalities. Figure

Phenothiazine is a heteroaromatic molecule capable of various noncovalent interactions, including halogen bonding and π-stacked association. Despite its broad use in functional materials and pharmaceutical ingredients, a systematic comparison of these interaction modes has been lacking. Here, we report a combined experimental and computational study of intermolecular interactions of phenothiazine with a prototypical halogen-bond (HaB) donor (tetrabromomethane), planar π-electron acceptors (tetracyanopyrazine and tetrafluoro-p-benzoquinone), and multifunctional species capable of both interaction types (iodo- and bromo-3,5-dinitrobenzenes). X-ray structural analysis revealed that CBr4 forms exclusively C–Br···π halogen bonds with the aromatic rings of phenothiazine, whereas all π-acceptors yield alternating donor–acceptor stacks characterized by multiple short contacts indicative of multicenter interactions. Notably, co-crystals of iodo- and bromodinitrobenzenes with phenothiazine display only π-stacked architectures. Density-functional calculations showed that isolated HaB complexes involving N, S, or π sites of phenothiazine possess comparable binding energies (≈−3 kcal mol−1), whereas π-stacked complexes are substantially stronger (≈−9–12 kcal mol−1). QTAIM, NCI, NBO, and energy-decomposition analyses indicated that while amounts of charge transfer in halogen-bonded and π-stacked complexes are comparable, the enhanced stability of the latter originates primarily from a large dispersion contribution. These results rationalize the solid-state preference for π-stacking over halogen bonding in systems where both motifs are accessible and clarify the hierarchy and physical origin of noncovalent interactions involving phenothiazine, providing guidance for the design of supramolecular assemblies and functional materials based on this versatile electron donor.

Sentiment analysis (SA) has grown considerably in organizational science research over the past two decades, particularly in the last few years. While enthusiasm for integrating advanced natural language processing algorithms is encouraging, authors are not reaping the benefits of such tools fully. Our systematic review of SA application in the organizational sciences suggests that authors struggle to appreciate all of the decisions that are inherent to SA, the choices that are available at each decision point, and the consequences of each choice. To address this gap, we use a working example to illustrate four critical decision points authors confront when conducting SA, and the subsequent impact different choices can have on one's conclusion. Decision points include selecting the SA method, computing a sentiment score, preprocessing the data, and using an appropriate level of analysis. We conclude with a framework outlining five dimensions (e.g., accuracy, interpretability, computational cost) to guide the selection of an SA approach based on study goals and needs, along with seven recommendations to authors wishing to apply SA.

This chapter discusses the application of Applied Behavior Analysis (ABA) in teaching office skills to persons with intellectual disabilities (ID). Emphasis is placed on task analysis to break down complex office tasks into manageable steps, chaining to systematically connect these steps into functional sequences, and shaping to gradually build proficiency by reinforcing successive approximations. Reinforcement serves as a cornerstone strategy, motivating learners and strengthening desired behaviors. By applying these techniques, individuals with ID can acquire practical office competencies that enhance independence, employability, and workplace integration. The chapter underscores how structured, evidence-based instruction not only promotes skill mastery but also fosters confidence and meaningful participation in professional environments for persons with intellectual disabilities.

The “math as male” stereotype is societally pervasive and emerges early in development. However, math is a broad and multifaceted domain that requires proficiency in several different cognitive skills. The current study explored the gender stereotypes associated with toys linked to the cognitive skills of numeracy, spatial reasoning, and patterning. Across three studies (N = 878), adults viewed toys associated with each cognitive skill and reported who would prefer them: boys, girls, U.S. parents buying for boys versus girls, and self as a child. The gendering of toys varied by toy. The most consistent alignment was between spatial reasoning toys and boys. Results for numeracy and patterning toys were more mixed, but sometimes neutral or female-leaning. There also tended to be a shift when reporting about others’ preferences versus own preferences, with a weaker male stereotype for the latter. Understanding how adults associate these cognitive skills with gender has important implications for research in mathematics education and belonging within STEM fields.

The concept of density is difficult for students to understand because it cannot be directly observed. To gain a deeper understanding of this concept, students need to learn about density at the microscopic and macroscopic levels. Virtual Reality (VR) provides an opportunity for students to experience the phenomena at both levels. A density exploration simulation was used in a Cave Automatic Virtual Environment (CAVE) to investigate the impact of the CAVE on preservice teachers' understanding of density. Three preservice teachers were interviewed before and after their CAVE experience on the concept of density. The data collected consisted of participants' recorded audio responses, written texts, and drawings made during the interviews. Thematic analysis was used to examine the raw data, and three major themes emerged regarding participants' understanding of the concept of density. The experience helped participants visualize water and oil molecules, recognize differences in molecular structures, explore the role of intermolecular forces in determining water density, and observe that air does not affect ice density at the microscopic scale. The study suggests that students can benefit from VR experiences such as those in the CAVE to explore density at macroscopic and microscopic levels.