An official website of the United States government
How traits at multiple levels of biological organization evolve in a correlated fashion in response to directional selection is poorly understood, but two popular models are the very general “behavior evolves first” (BEF) hypothesis and the more specific “morphology-performance-behavior-fitness” (MPBF) paradigm. Both acknowledge that selection often acts relatively directly on behavior and that when behavior evolves, other traits will as well but most with some lag. However, this proposition is exceedingly difficult to test in nature. Therefore, we studied correlated responses in the high-runner (HR) mouse selection experiment, in which four replicate lines have been bred for voluntary wheel-running behavior and compared with four non-selected control (C) lines. We analyzed a wide range of traits measured at generations 20–24 (with a focus on new data from generation 22), coinciding with the point at which all HR lines were reaching selection limits (plateaus). Significance levels (226 P values) were compared across trait types by ANOVA, and we used the positive false discovery rate to control for multiple comparisons. This meta-analysis showed that, surprisingly, the measures of performance (including maximal oxygen consumption during forced exercise) showed no evidence of having diverged between the HR and C lines, nor did any of the life history traits (e.g., litter size), whereas body mass had responded (decreased) at least as strongly as wheel running. Overall, results suggest that the HR lines of mice had evolved primarily by changes in motivation rather than performance ability at the timethey were reaching selection limits. In addition, neither the BEF model nor the MPBF model of hierarchical evolution provides a particularly good fit to theHRmouse selection experiment.
more »
« less
Reconstructing the invention of the wheel using computational structural analysis and design
The invention of the wheel is widely credited as a pivotal moment in human history, yet the details surrounding its discovery are shrouded in mystery. There remains no scholarly consensus on key questions such as where, how and by whom this technology was originally invented. In this study, we employ state-of-the-art techniques from computational structural mechanics to shed light on this long-standing puzzle. Based on this analysis, we propose a probable path along which the wheel evolved via a sequence of three major innovations. We also introduce an original computational design algorithm that autonomously generates a wheel-and-axle system using an evolutionary process that offers insight into the way in which the first wheels likely evolved nearly 6000 years ago. Our analysis provides new supporting evidence for the recently advanced theory that the wheel was invented by Neolithic miners harvesting copper ore from the Carpathian Mountains as early as 3900 BC. Moreover, we show how the discovery of the wheel was made possible by the unique physical features of the mine environment, whose impact was analogous to the selective environmental pressures that drive biological evolution.
more »
« less
- Award ID(s):
- 2311078
- PAR ID:
- 10568812
- Publisher / Repository:
- The Royal Society
- Date Published:
- Journal Name:
- Royal Society Open Science
- Volume:
- 11
- Issue:
- 10
- ISSN:
- 2054-5703
- Subject(s) / Keyword(s):
- Computational design History of Technology Invention of the Wheel
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This paper reports on the electromagnetic analysis and experimental testing of a newly invented six-degree of freedom electrodynamic wheel (EDW) magnetic levitation (maglev) vehicle that can stably levitate over a passive low-cost U-guideway. The U-guideway is composed of two sections of L-track aluminum sheet. Both a radial and an axial proof-of-principle EDW maglev vehicle has been built and experimentally tested. The EDW-maglev vehicle contains four one pole-pair diametric magnetized magnets that are driven using a low-cost motor and motor controller. No advanced controls are needed to provide basic stability. A 3-D transient finite element analysis model was used to study the 3-D forces created when the magnets are rotated over the aluminum L-track. The track design study showed that in addition to providing lateral recentering force the L-track can also be used to increases thrust and lift force.more » « less
-
Abstract The nutrient artery provides ~50%–70% of the total blood volume to long bones in mammals. Studying the functional characteristics of this artery in vivo can be difficult and expensive, so most researchers have measured the nutrient foramen, an opening on the outer surface of the bone that served as the entry point for the nutrient artery during development and bone ossification. Others have measured the nutrient canal (i.e., the passage which the nutrient artery once occupied), given that the external dimensions of the foramen do not necessarily remain uniform from the periosteal surface to the medullary cavity. The nutrient canal, as an indicator of blood flow to long bones, has been proposed to provide a link to studying organismal activity (e.g., locomotor behavior) from skeletal morphology. However, although external loading from movement and activity causes skeletal remodeling, it is unclear whether it affects the size or configuration of nutrient canals. To investigate whether nutrient canals can exhibit phenotypic plasticity in response to physical activity, we studied a mouse model in which four replicate high runner (HR) lines have been selectively bred for high voluntary wheel‐running behavior. The selection criterion is the average number of wheel revolutions on days 5 and 6 of a 6‐day period of wheel access as young adults (~6–8 weeks old). An additional four lines are bred without selection to serve as controls (C). For this study, 100 female mice (half HR, half C) from generation 57 were split into an active group housed with wheels and a sedentary group housed without wheels for 12 weeks starting at ~24 days of age. Femurs were collected, soft tissues were removed, and femora were micro‐computed tomography scanned at a resolution of 12 μm. We then imported these scans into AMIRA and created 3D models of femoral nutrient canals. We tested for evolved differences in various nutrient canal traits between HR and C mice, plastic changes resulting from chronic exercise, and the selection history‐by‐exercise interaction. We found few differences between the nutrient canals of HR versus C mice, or between the active and sedentary groups. We did find an interaction between selection history and voluntary exercise for the total number of nutrient canals per femur, in which wheel access increased the number of canals in C mice but decreased it in HR mice. Our results do not match those from an earlier study, conducted at generation 11, which was prior to the HR lines reaching selection limits for wheel running. The previous study found that mice from the HR lines had significantly larger total canal cross‐sectional areas compared to those from C lines. However, this discrepancy is consistent with studies of other skeletal traits, which have found differences between HR and C mice to be somewhat inconsistent across generations, including the loss of some apparent adaptations with continued selective breeding after reaching a selection limit for wheel‐running behavior.more » « less
-
Prior research has shown that digital games can enhance STEM education by providing learners with immersive and authentic scientific experiences. However, optimizing the learning outcomes of students engaged in game-based environments requires aligning the game design with diverse student needs. Therefore, an in-depth understanding of player behavior is crucial for identifying students who need additional support or modifications to the game design. This study applies an Ordered Network Analysis (ONA)—a specific kind of Epistemic Network Analysis (ENA)—to examine the game trace log data of student interactions, to gain insights into how learning gains relate to the different ways that students move through an open-ended virtual world for learning microbiology. Our findings reveal that differences between students with high and low learning gains are mediated by their prior knowledge. Specifically, level of prior knowledge is related to behaviors that resemble wheel-spinning, which warrant the development of future interventions. Results also have implications for discovery with modeling approaches and for enhancing in-game support for learners and improving game design.more » « less
-
rior research has shown that digital games can enhance STEM education by providing learners with immersive and authentic scientific experiences. However, optimizing the learning outcomes of students engaged in game-based environments requires aligning the game design with diverse student needs. Therefore, an in-depth understanding of player behavior is crucial for identifying students who need additional support or modifications to the game design. This study applies an Ordered Network Analysis (ONA)—a specific kind of Epistemic Network Analysis (ENA)—to examine the game trace log data of student interactions, to gain insights into how learning gains relate to the different ways that students move through an open-ended virtual world for learning microbiology. Our findings reveal that differences between students with high and low learning gains are mediated by their prior knowledge. Specifically, level of prior knowledge is related to behaviors that resemble wheel-spinning, which warrant the development of future interventions. Results also have implications for discovery with modeling approaches and for enhancing in-game support for learners and improving game design.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1098/rsos.240373
