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1. Design and Implementation of Experiential Learning Modules for Geotechnical Engineering

   Kershaw, Kyle; Luna, Ronaldo; Carroll, J. Chris; Lovell, Matthew D. (January 2021, ASEE annual conference exposition)

   null (Ed.)

   Geotechnical engineering undergraduate curriculum typically consist of courses in soil mechanics and foundation design that include a variety of topics that are difficult for students to understand and master. Behavior of the below grade natural and built geomaterials discussed in these courses can be difficult for students to visualize. Typically, the mechanisms of behavior are demonstrated using small-scale laboratory tests, two-dimensional sketches, simple table-top models, or video simulations in the classroom. Students rarely have the opportunity to observe large-scale behavior of foundations in the field or laboratory. The authors from Rose-Hulman Institute of Technology and Saint Louis University designed and implemented a large-scale foundation testing system to address several topics that students tend to struggle with the most, including 1) the difference in strength and service limit states in shallow foundation design, 2) soil-structure interaction associated with lateral behavior of deep foundations, and 3) the influence of near-surface soil on lateral behavior of deep foundations. This paper provides a detailed overview of the design, fabrication, and implementation of two large-scale experiential learning modules for undergraduate courses in soil mechanics and foundation engineering. The first module utilizes shallow foundations in varying configurations to demonstrate the differences in strength and service limit state behavior of shallow foundations. The second module utilizes a relatively flexible pile foundation embedded in sand to demonstrate the lateral behavior of deep foundations. The first module was used in the soil mechanics courses at Rose-Hulman Institute of Technology and Saint Louis University to compare theoretical and observed behavior of shallow foundations. The second module was used in the foundation engineering course at Rose-Hulman Institute of Technology to illustrate the concepts of soil-structure interaction and the influence of near-surface soil on lateral behavior of deep foundations. 

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2. Political ideologies and moral foundations of engineering professionals in the United States

   https://doi.org/10.1016/j.techsoc.2023.102379  

   Kim, Dayoung; Jesiek, Brent K (October 2023, Technology in Society)

   Scholars have argued that engineering practice should be understood in its societal context, including the political contexts in which engineers perform. However, very few research studies have systematically explored the political and moral backgrounds of engineering professionals, who would be the main agents in the political contexts. This paper reports our exploratory study of the political ideologies and moral foundations of engineers in the United States. Based on survey responses from 515 engineers, we conducted generalized ordinal logistic regression analyses and multiple linear regression analyses to examine how engineers’ political ideologies are associated with their moral foundations and how engineers’ political ideologies and moral foundations vary across their employment sectors, organizational positions, and demographic attributes. We found that engineers in the manufacturing sector are more politically conservative than engineers in the computer/electronics/IT sector. Additionally, engineers in higher positions in their organizations are more politically conservative than engineers in lower positions, and female engineers are more politically liberal than male engineers. We also found that engineers’ endorsement of the five moral foundations differs by sector and demographic attributes. Moreover, engineers’ moral foundations substantially explain engineers’ political ideologies, consistent with previous studies using the Moral Foundations Theory. 

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3. Classifying photonic topology using the spectral localizer and numerical K -theory

   https://doi.org/10.1063/5.0239018  

   Cerjan, Alexander; Loring, Terry_A (November 2024, APL Photonics)

   Recently, the spectral localizer framework has emerged as an efficient approach for classifying topology in photonic systems featuring local nonlinearities and radiative environments. In nonlinear systems, this framework provides rigorous definitions for concepts such as topological solitons and topological dynamics, where a system’s occupation induces a local change in its topology due to nonlinearity. For systems embedded in radiative environments that do not possess a shared bulk spectral gap, this framework enables the identification of local topology and shows that local topological protection is preserved despite the lack of a common gap. However, as the spectral localizer framework is rooted in the mathematics of C*-algebras, and not vector bundles, understanding and using this framework requires developing intuition for a somewhat different set of underlying concepts than those that appear in traditional approaches for classifying material topology. In this tutorial, we introduce the spectral localizer framework from a ground-up perspective and provide physically motivated arguments for understanding its local topological markers and associated local measure of topological protection. In doing so, we provide numerous examples of the framework’s application to a variety of topological classes, including crystalline and higher-order topology. We then show how Maxwell’s equations can be reformulated to be compatible with the spectral localizer framework, including the possibility of radiative boundary conditions. To aid in this introduction, we also provide a physics-oriented introduction to multi-operator pseudospectral methods and numerical K-theory, two mathematical concepts that form the foundation for the spectral localizer framework. Finally, we provide some mathematically oriented comments on the C*-algebraic origins of this framework, including a discussion of real C*-algebras and graded C*-algebras that are necessary for incorporating physical symmetries. Looking forward, we hope that this tutorial will serve as an approachable starting point for learning the foundations of the spectral localizer framework. 

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4. Probabilistic Species Tree Distances: Implementing the Multispecies Coalescent to Compare Species Trees Within the Same Model-Based Framework Used to Estimate Them

   https://doi.org/10.1093/sysbio/syz031  

   Adams, Richard H; Castoe, Todd A; Burbrink, Frank (May 2019, Systematic Biology)

   Abstract Despite the ubiquitous use of statistical models for phylogenomic and population genomic inferences, this model-based rigor is rarely applied to post hoc comparison of trees. In a recent study, Garba et al. derived new methods for measuring the distance between two gene trees computed as the difference in their site pattern probability distributions. Unlike traditional metrics that compare trees solely in terms of geometry, these measures consider gene trees and associated parameters as probabilistic models that can be compared using standard information theoretic approaches. Consequently, probabilistic measures of phylogenetic tree distance can be far more informative than simply comparisons of topology and/or branch lengths alone. However, in their current form, these distance measures are not suitable for the comparison of species tree models in the presence of gene tree heterogeneity. Here, we demonstrate an approach for how the theory of Garba et al. (2018), which is based on gene tree distances, can be extended naturally to the comparison of species tree models. Multispecies coalescent (MSC) models parameterize the discrete probability distribution of gene trees conditioned upon a species tree with a particular topology and set of divergence times (in coalescent units), and thus provide a framework for measuring distances between species tree models in terms of their corresponding gene tree topology probabilities. We describe the computation of probabilistic species tree distances in the context of standard MSC models, which assume complete genetic isolation postspeciation, as well as recent theoretical extensions to the MSC in the form of network-based MSC models that relax this assumption and permit hybridization among taxa. We demonstrate these metrics using simulations and empirical species tree estimates and discuss both the benefits and limitations of these approaches. We make our species tree distance approach available as an R package called pSTDistanceR, for open use by the community. 

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5. The other side of tropical forest drought: do shallow water table regions of Amazonia act as large‐scale hydrological refugia from drought?

   https://doi.org/10.1111/nph.17914  

   Costa, Flavia R. C.; Schietti, Juliana; Stark, Scott C.; Smith, Marielle N. (January 2022, New Phytologist)

   Summary Tropical forest function is of global significance to climate change responses, and critically determined by water availability patterns. Groundwater is tightly related to soil water through the water table depth (WT), but historically neglected in ecological studies. Shallow WT forests (WT < 5 m) are underrepresented in forest research networks and absent in eddy flux measurements, although they representc. 50% of the Amazon and are expected to respond differently to global‐change‐related droughts. We review WT patterns and consequences for plants, emerging results, and advance a conceptual model integrating environment and trait distributions to predict climate change effects. Shallow WT forests have a distinct species composition, with more resource‐acquisitive and hydrologically vulnerable trees, shorter canopies and lower biomass than deep WT forests. During ‘normal’ climatic years, shallow WT forests have higher mortality and lower productivity than deep WT forests, but during moderate droughts mortality is buffered and productivity increases. However, during severe drought, shallow WT forests may be more sensitive due to shallow roots and drought‐intolerant traits. Our evidence supports the hypothesis of neglected shallow WT forests being resilient to moderate drought, challenging the prevailing view of widespread negative effects of climate change on Amazonian forests that ignores WT gradients, but predicts they could collapse under very strong droughts. 

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