From single attitudes to belief systems: Examining the centrality of STEM attitudes using belief network analysis

Many achievement and motivation theories claim that a specific set of beliefs, interests or values plays a central role in determining career choice and behavior. In order to investigate how attitudes determine behaviors, researchers generally investigate each attitude in isolation. This article argues that studying belief systems rather than single attitudes has several explanatory advantages. In particular, a system-level approach can provide clear definitions and measures of attitude importance. Using a nationally representative sample of 13,283 9th graders and measures of 136 STEM-related attitudes, I implement a belief network analysis to investigate which attitudes are most influential in determining STEM career choice. The results suggest that identity beliefs, educational expectations and ability-related beliefs play central roles in individuals’ belief systems

Assault, Robbery, Mayhem: The Consequences Of Fraternal Campus Loyalty Movements At The University Of Kansas After World War I

Submitted to the Department of History of the University of Kansas in partial fulfillment of the requirements for departmental honors

Filtration of Gene Trees From 9,000 Exons, Introns, and UCEs Disentangles Conflicting Phylogenomic Relationships in Tree Frogs (Hylidae)

An emerging challenge in interpreting phylogenomic data sets is that concatenation and multi-species coalescent summary species tree approaches may produce conflicting results. Concatenation is problematic because it can strongly support an incorrect topology when incomplete lineage sorting (ILS) results in elevated gene-tree discordance. Conversely, summary species tree methods account for ILS to recover the correct topology, but these methods do not account for erroneous gene trees (“EGTs”) resulting from gene tree estimation error (GTEE). Third, site-based and full-likelihood methods promise to alleviate GTEE as these methods use the sequence data from alignments. To understand the impact of GTEE on species tree estimation in Hylidae tree frogs, we use an expansive data set of ∼9,000 exons, introns, and ultra-conserved elements and initially found conflict between all three types of analytical methods. We filtered EGTs using alignment metrics that could lead to GTEE (length, parsimony-informative sites, and missing data) and found that removing shorter, less informative alignments reconciled the conflict between concatenation and summary species tree methods with increased gene concordance, with the filtered topologies matching expected results from past studies. Contrarily, site-based and full-likelihood methods were mixed where one method was consistent with past studies and the other varied markedly. Critical to other studies, these results suggest a widespread conflation of ILS and GTEE, where EGTs rather than ILS are driving discordance. Finally, we apply these recommendations to an R package named PhyloConfigR, which facilitates phylogenetic software setup, summarizes alignments, and provides tools for filtering alignments and gene trees

Crystal structures of di-μ-chlorido-bis­({(E)-5-(ethyl­amino)-4-methyl-2-[(pyridin-2-yl)diazen­yl]phen­o­lato}copper(II)) and chlorido­bis­(1,10-phen­anthroline)copper(II) chloride tetra­hydrate

The dark-red title complex crystallized from an equimolar methanol solution of (E)-5-(ethyl­amino)-4-methyl-2-[(pyridin-2-yl)diazen­yl]phenol and CuCl2(phen) (phen = 1,10-phenanthroline) as a centrosymmetric dimer, [CuCl(C14H15N4O)]2. The Cu atoms are bridged by two Cl ligands and have a slightly distorted square-pyramidal coordination, where two N atoms from the azo and the pyridine moieties, a phenolic O and a Cl atom comprise the base and the other Cl occupies the apex position. The apical Cu—Cl bond, 2.6192 (4) Å, is longer than the basal one, 2.2985 (3) Å, due to Jahn–Teller distortion. The dimers are associated via weak inter­molecular hydrogen bonds and π–π stacking inter­actions between phenyl and pyridine rings. A monomeric by-product of the same reaction, [CuCl(phen)2]Cl·4H2O, has a trigonal–bipyramidal coordination of Cu with equatorial Cl ligand, and extensive outer-sphere disorder. In the structure of 4, the packing of cations leaves continuous channels containing disordered Cl− anions and solvent mol­ecules. The identity of the solvent (water or a water/methanol mixture) was not certain. The disordered anion/solvent regions comprise 28% of the unit-cell volume. The disorder was approximated by five partly occupied positions of the Cl− anion and ten positions of O atoms with a total occupancy of 3, giving a total of 48 electrons per asymmetric unit, in agreement with the integral electron density of 47.8 electrons in the disordered region, as was estimated using the BYPASS-type solvent-masking program [van der Sluis & Spek (1990). Acta Cryst. A46, 194–201]

Assessing Breast Cancer Molecular Subtypes Using Extracellular Vesicles’ mRNA

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Analytical Chemistry, copyright © 2023 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.analchem.3c00624.Extracellular vesicles (EVs) carry RNA cargo that is believed to be associated with the cell-of-origin and thus have the potential to serve as a minimally invasive liquid biopsy marker for supplying molecular information to guide treatment decisions (i.e., precision medicine). We report the affinity isolation of EV subpopulations with monoclonal antibodies attached to the surface of a microfluidic chip that is made from a plastic to allow for high-scale production. The EV microfluidic affinity purification (EV-MAP) chip was used for the isolation of EVs sourced from two-orthogonal cell types and was demonstrated for its utility in a proof-of-concept application to provide molecular subtyping information for breast cancer patients. The orthogonal selection process better recapitulated the epithelial tumor microenvironment by isolating two subpopulations of EVs: EVEpCAM (epithelial cell adhesion molecule, epithelial origin) and EVFAPα (fibroblast activation protein α, mesenchymal origin). The EV-MAP provided recovery >80% with a specificity of 99 ± 1% based on exosomal mRNA (exo-mRNA) and real time–droplet digital polymerase chain reaction results. When selected from the plasma of healthy donors and breast cancer patients, EVs did not differ in size or total RNA mass for both markers. On average, 0.5 mL of plasma from breast cancer patients yielded ∼2.25 ng of total RNA for both EVEpCAM and EVFAPα, while in the case of cancer-free individuals, it yielded 0.8 and 1.25 ng of total RNA from EVEpCAM and EVFAPα, respectively. To assess the potential of these two EV subpopulations to provide molecular information for prognostication, we performed the PAM50 test (Prosigna) on exo-mRNA harvested from each EV subpopulation. Results suggested that EVEpCAM and EVFAPα exo-mRNA profiling using subsets of the PAM50 genes and a novel algorithm (i.e., exo-PAM50) generated 100% concordance with the tumor tissue

Coupled Lattice Boltzmann Modeling Framework for Pore-Scale Fluid Flow and Reactive Transport

In this paper, we propose a modeling framework for pore-scale fluid flow and reactive transport based on a coupled lattice Boltzmann model (LBM). We develop a modeling interface to integrate the LBM modeling code parallel lattice Boltzmann solver and the PHREEQC reaction solver using multiple flow and reaction cell mapping schemes. The major advantage of the proposed workflow is the high modeling flexibility obtained by coupling the geochemical model with the LBM fluid flow model. Consequently, the model is capable of executing one or more complex reactions within desired cells while preserving the high data communication efficiency between the two codes. Meanwhile, the developed mapping mechanism enables the flow, diffusion, and reactions in complex pore-scale geometries. We validate the coupled code in a series of benchmark numerical experiments, including 2D single-phase Poiseuille flow and diffusion, 2D reactive transport with calcite dissolution, as well as surface complexation reactions. The simulation results show good agreement with analytical solutions, experimental data, and multiple other simulation codes. In addition, we design an AI-based optimization workflow and implement it on the surface complexation model to enable increased capacity of the coupled modeling framework. Compared to the manual tuning results proposed in the literature, our workflow demonstrates fast and reliable model optimization results without incorporating pre-existing domain knowledge

Patient Selection and Impacts of Plan Choice on Specialty, Urgent Care Center and Emergency Department Visits and Total Expenditures when Families Choose between a Direct Primary Care Option and a Traditional Option for Employee Medical Benefits

Introduction Two of the most difficult and seemingly intractable problems in US health care are high expenditures and the state of primary care. Direct primary care (DPC) is a newer approach to primary care delivery in which patients or employers pay directly for unlimited access to a broad, defined set of primary care services; insurance is not used for primary care. DPC may improve the delivery of primary care in ways that reduce overall utilization and spending and benefit patients and physicians.Purpose This dissertation aimed to determine factors associated with plan selection and quantify effects of plan selection on health care utilization and expenditures when an employer adds a DPC option to its medical benefit offering.Data and Methods Data was from a large employer group in which a DPC option was added to a typical PPO option (the “Standard” plan). The two plans differed only in elements related to primary care delivery and enrollees who chose DPC were required to switch to a DPC physician for primary care.The selection aim used logistic regression at the family level to examine the plan selected when DPC was first offered. The utilization and expenditures aims used two period multiple linear regression difference in differences at the member level, examined 18 months before and 39 months after DPC was first offered. Expenditures excluded pharmaceutical costs and included DPC fees.Results Plan choice was statistically significantly associated with enrollee age, enrollee race/ethnicity, presence of chronic conditions in the family (CCs) and presence of a usual source of care in the family (USC). DPC enrollees were more likely to be younger, white or other race/ethnicity, without CCs and without a USC.DPC statistically significantly increased specialist visits. Some results indicated that DPC may have lowered urgent care center (UCC) and emergency department (ED) visits but were inconclusive in the main analyses. DPC increased expenditures and this result was statistically significant when members with the top 1% of expenditures were excluded but not when they were included.CCs and USC were consistently the most statistically significant control variables and had the largest effect size compared to the size of the difference in differences result. Member age was also statistically significant for utilization and expenditure aims.Conclusions In contrast to studies of DPC and similar primary care models, this study did not show DPC reduced ED visits or expenditures. Selection results align with prior studies. The relevance of age, CCs and USC for plan choice, utilization and expenditures aligns with prior research. Future DPC research should examine plan selection, utilization and expenditures over time by year to allow employees more time to consider the new DPC option and to allow changes to doctor-patient relationship and health over time to emerge. Future research of specialist visits should consider that new patients likely experience different referral patterns than existing patients, which would impact specialist visits for DPC but not Standard enrollees. The level of DPC fees should be examined for its effect on expenditures. More research is needed to determine whether and when DPC can reduce utilization and spending

Ligand Gaussian Accelerated Molecular Dynamics 2 (LiGaMD2): Improved Calculations of Ligand Binding Thermodynamics and Kinetics with Closed Protein Pocket

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Chemical Theory and Computation, Copyright © 2023 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jctc.2c01194.Ligand binding thermodynamics and kinetics are critical parameters for drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics from molecular simulations due to limited simulation timescales. Protein dynamics, especially in the ligand binding pocket, often plays an important role in ligand binding. Based on our previously developed Ligand Gaussian accelerated molecular dynamics (LiGaMD), here we present LiGaMD2 in which a selective boost potential was applied to both the ligand and protein residues in the binding pocket to improve sampling of ligand binding and dissociation. To validate the performance of LiGaMD2, the T4 lysozyme (T4L) mutants with open and closed pockets bound by different ligands were chosen as model systems. LiGaMD2 could efficiently capture repetitive ligand dissociation and binding within microsecond simulations of all T4L systems. The obtained ligand binding kinetic rates and free energies agreed well with available experimental values and previous modeling results. Therefore, LiGaMD2 provides an improved approach to sample opening of closed protein pockets for ligand dissociation and binding, thereby allowing for efficient calculations of ligand binding thermodynamics and kinetics

Repatriation Beyond the Borderlands: The Impact of the Depression of 1921 on Kansas City's Mexican Immigrants During the Great Depression

Submitted to the Department of History of the University of Kansas in partial fulfillment of the requirements for departmental honors.During the Great Depression, federal, state, and local authorities throughout the United States utilized large-scale deportation raids and repatriation to eject an estimated 400,000 Mexicans and Mexican-Americans from the country. While previous studies of Mexican repatriation during the Great Depression focus on larger communities near the U.S.-Mexico border, there are very few academic discussions of what repatriation looked like in the Midwest and beyond. The Kansas City metropolitan area contains one of the largest communities of Mexican immigrants in the United States outside of the borderlands. Unlike in Los Angeles, San Antonio, or even Chicago, authorities in Kansas City used large-scale Mexican repatriation in Kansas City prior to the Great Depression, and ultimately learned that repatriation is a temporary solution to a perennial issue. This senior thesis analyzes how Kansas City authorities used repatriation during the Depression of 1921, the ineffectiveness of repatriation in slowing the growth of the Kansas City barrio, and the community-building that took place between 1921 and 1929 that proved crucial to the staying power of Mexicans in Kansas City through the Great Depression

The networked micro-decision context: A new lens on transformative urban governance

Recent large-scale societal disruptions, from the COVID-19 pandemic to intensifying wildfires and weather events, reveal the importance of transforming governance systems so they can address complex, transboundary, and rapidly evolving crises. Yet current knowledge of the decision-making dynamics that yield transformative governance remains scant. Studies typically focus on the aggregate outputs of government decisions, while overlooking their micro-level underpinnings. This is a key oversight because drivers of policy change, such as learning or competition, are prosecuted by people rather than organizations. We respond to this knowledge gap by introducing a new analytical lens for understanding policymaking, aimed at uncovering how characteristics of decision-makers and the structure of their relationships affect their likelihood of effectuating transformative policy responses. This perspective emphasizes the need for a more dynamic and relational view on urban governance in the context of transformation