Race Yourselves: A Longitudinal Exploration of Self-Competition Between Past, Present, and Future Performances in a VR Exergame

Participating in competitive races can be a thrilling experience for athletes, involving a rush of excitement and sensations of flow, achievement, and self-fulfilment. However, for non-athletes, the prospect of competition is often a scary one which affects intrinsic motivation negatively, especially for less fit, less competitive individuals. We propose a novel method making the positive racing experience accessible to non-athletes using a high-intensity cycling VR exergame: by recording and replaying all their previous gameplay sessions simultaneously, including a projected future performance, players can race against a crowd of "ghost" avatars representing their individual fitness journey. The experience stays relevant and exciting as every race adds a new competitor. A longitudinal study over four weeks and a cross-sectional study found that the new method improves physical performance, intrinsic motivation, and flow compared to a non-competitive exergame. Additionally, the longitudinal study provides insights into the longer-term effects of VR exergames

Weather During Key Growth Stages Explains Grain Quality and Yield of Maize

Maize (Zea mays L.) grain yield and compositional quality are interrelated and are highly influenced by environmental factors such as temperature, total precipitation, and soil water storage. Our aim was to develop a regression model to account for this relationship among grain yield and compositional quality traits across a large geographical region. Three key growth periods were used to develop algorithms based on the week of emergence, the week of 50% silking, and the week of maturity that enabled collection and modeling of the effect of weather and climatic variables across the major maize growing region of the United States. Principal component analysis (PCA), stepwise linear regression models, and hierarchical clustering analyses were used to evaluate the multivariate relationship between weather, grain quality, and yield. Two PCAs were found that could identify superior grain compositional quality as a result of ideal environmental factors as opposed to low-yielding conditions. Above-average grain protein and oil levels were favored by less nitrogen leaching during early vegetative growth and higher temperatures at flowering, while greater oil than protein concentrations resulted from lower temperatures during flowering and grain fill. Water availability during flowering and grain fill was highly explanatory of grain yield and compositional quality

The Team Personality–Team Performance Relationship Revisited: The Impact of Criterion Choice, Pattern of Workflow, and Method of Aggregation

Using meta-analytic evidence, this study tested trait- and task-based theoretical approaches to team personality management, using both team behaviors and team outcomes as criteria. Trait theories state that maximization of the team trait is harmful for Extroversion (complementary team fit) but beneficial for Conscientiousness, Agreeableness, and Emotional Stability (supplementary fit). Task-based theories state that tasks with few work exchanges are best reflected by mean trait scores, whereas tasks with frequent work exchanges are best represented by other types of scores (e.g., minimum score). Correlations between different aggregations of team personality and team performance were coded, as well as the study criterion choice and the pattern of workflow (as moderators). Partial support for both trait and task theories were found. Team Conscientiousness and Agreeableness provided supplementary fit primarily with team behaviors, but there was mixed evidence that Extroversion provided complementary fit. Furthermore, minimum and variance measures of the team trait related to team performance in tasks with frequent work exchanges, but not in tasks with few work exchanges. Results suggest several limitations with existing measurement methods, which are discussed