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Controlling Oxygen Speciation through Forced Dynamic Operation of Chemical Reactors During Ethane Oxidative Dehydrogenation
No full textForced dynamic operation (FDO) has been of recent interest to enhance chemical reactor performance beyond what is achievable via conventional steady state operation (SSO). Selective oxidation reactions are one chemistry that has demonstrated elevated selectivities through FDO. Hypotheses suggest that FDO promotes reactions with selective lattice oxygen while suppressing chemisorbed oxygen reliant unselective pathways. Herein, through a combination of experiments, modeling, and theory, this study investigates the use of FDO as a strategy to control catalytically stored oxygen speciation and thus reactor performance during the oxidative dehydrogenation of ethane to ethylene (ODHE). Theoretical calculations demonstrate that multicomponent FDO performance is directly linked to apparent reaction orders of the modulated species. For instance, dynamic experiments suggest that FDO selectivity enhancement is achievable when unselective reactions are more sensitive to the modulated element than selective pathways. In fact, FDO can even reduce diffusion induced selectivity losses encountered within industrially sized (diffusion limited) catalyst pellets for reactions in series. Reactor modeling results indicate that selectivity gains and conversion losses experienced during FDO are indeed directly linked to the oxygen speciation and concentration respectively within the metal oxide catalyst which can be tuned via oscillation frequencies, amplitudes and cycle averages. Investigating degrees of rate control through bifurcations (multiplicity and Hopf) on isothermal catalyst surfaces offers a first step towards their interpretations during FDO. Linking performance to composition, kinetic and transport properties of staple metal oxide catalysts (VOx and MoOx) during ODHE yields a generalized method to identify selective oxidation catalysts and operating conditions where FDO supersedes traditional SSO
How Mind Wandering Relates to Reading in a Second Language
No full textBoth language and mind wandering have been strongly linked to reading, however there remains very scarce literature on their intersection. For instance, there are very few existing studies evaluating mind wandering in the context of reading in a second language in children, and none to our knowledge that explicitly evaluate the relationship of mind wandering and reading within the context of second-language reading. Therefore, the overarching goal of this project was to examine mind wandering and its role in regard to reading in a second language in a sample of at-risk middle school students with consideration of relevant language factors. The sample included 195 students enrolled in grade 6-8 and identified as struggling readers; approximately half were also designated as limited English proficient (LEP), with Spanish as their first language. Each student completed measures of mind wandering, reading, and other domains, and bilingual/LEP students also completed additional language measures in both English and Spanish. Results indicated that, contrary to hypotheses, bilingual/LEP students reported less mind wandering compared to non-LEP students, and mind wandering impacted reading outcomes minimally, and similarly, for bilingual/LEP students and non-LEP students. Within the group of bilingual/LEP students, some self-reported language measures were related to mind wandering, and there were some interactions of language variables and mind wandering for single word reading and reading fluency. Such effects appeared inconsistent and small in size, and so support was limited overall. Results extend work on mind wandering to children who are struggling readers. However, results highlight the role of language and literacy per se for these struggling readers, and that direct intervention is likely more impactful than attempting to ameliorate mind wandering in this group
Associations of Insecure Adult Attachment Style, Trauma-Related Social Cognition, and Emotion Regulation Difficulties with PTSD Symptom Severity among First Responders Who Served During Hurricane Harvey
No full textFirst responders play a vital role in response and recovery to natural disasters, and they are at a disproportionate risk for negative behavioral health outcomes following these events, including the development of posttraumatic stress disorder (PTSD) symptoms. Previous research has assessed PTSD symptoms and outcomes among first responders following various major hurricanes, but no study has examined the specific impact of Hurricane Harvey on first responders who were serving the region at the time. The association between insecure adult attachment style and PTSD symptom severity is well-established and has been documented among first responder populations. Understanding the social cognitive and affective factors implicated in the association between insecure adult attachment style and PTSD symptoms among first responders has the potential to inform specialized cognitive-behavioral treatments for this population. Trauma-related social cognition and emotion regulation difficulties (ERD) are factors with clinical relevance to both insecure adult attachment style and PTSD symptom severity. Few studies have examined the associations among these constructs in first responder populations. The present investigation examined the serial indirect effect of insecure adult attachment style (i.e., avoidant attachment; anxious attachment) on PTSD symptom severity through trauma-related social cognition and ERD. The sample was comprised of 115 first responders (Mage=42.25, SD=10.38, 80.0% male) who served during Hurricane Harvey in 2017 and were recruited from fire departments, emergency medical services (EMS) agencies, and law enforcement offices in the southern U.S. to complete an online survey in 2022. Avoidant adult attachment style was indirectly related to PTSD symptom severity via the sequential effects of trauma-related social cognition and ERD (β=.14, SE=.07, CI=.02-.31). The model including anxious adult attachment style as a statistical predictor was not significant (β=.10, SE=.07, CI=-.02-.28). The observed effects were evident after accounting for years of service as a first responder and trauma load. Post hoc exploratory analyses revealed that avoidant attachment styles are indirectly related to PTSD symptom severity through the sequential effects of negative cognitions about the world and ERD (β=.11, SE=.05, CI=.03-.22) as well as self-blame and ERD (β=.09, SE=.05, CI=.02-.21). Avoidant attachment styles did not demonstrate an indirect association with PTSD symptom severity through negative cognitions about the self and ERD (β=.12, SE=.08, CI=-.02-.30). Additional exploratory analyses revealed that avoidant attachment styles were indirectly related to PTSD negative alterations in cognitions and mood (β=.06, SE=.03, CI=.03-.20) as well as alterations in arousal and reactivity (β=.05, SE=.02, CI=.00-.10) through the sequential effects of trauma-related social cognition and ERD. Avoidant attachment styles did not demonstrate an indirect association with PTSD intrusion (β=.03, SE=.02, CI=-.00-.07) or avoidance (β=.01, SE=.01, CI=-.00-.03) symptom clusters as outcome variables. These findings suggest that there is merit in investigating the role of interpersonal factors and emotion regulation difficulties within first responder populations to inform evidence-based PTSD prevention and intervention efforts
Deep Learning-Based Emulation of Air Quality Models and Scenario-Based Vehicle Electrification Analysis across the contiguous United States
No full textAir pollution remains a significant environmental and public health concern, especially with urban growth and changing transportation emissions. This dissertation examines the air quality impacts of vehicle electrification and proposes deep learning methods to accelerate chemical transport modeling for timely policy support. In the first chapter, a Well-To-Wheel emissions analysis is conducted for four major U.S. cities—New York City, Los Angeles, Chicago, and Houston—under three 2035 vehicle electrification scenarios: moderate (MedE), high (HighE), and full (FullE). The framework combines GREET and MOVES using electricity projections from EIA and NREL. Results show average reductions in CO by 15.8% (MedE), 26.5% (HighE), and 99.1% (FullE), and in NOX by 5%, 8.5%, and 97.3%, respectively. GHG emissions decrease by up to 91% in FullE, while PM reductions remain modest due to non-exhaust sources. SOX emissions vary by region and grid mix, increasing in Houston under EIA but decreasing under NREL. In the second chapter, an emulator of the CMAQ model is developed using a 1D Convolutional Neural Network (CNN) to predict hourly surface NO2 concentrations over major Texas cities. Inputs match CMAQ and include emissions, meteorology, and land use data. The model is trained on summers of 2011 and 2014 and tested on summer 2017, achieving an Index of Agreement (IOA) of 0.95 and a correlation coefficient (R) of 0.90. The emulator predicts NO2 over 900 times faster than CMAQ, enabling rapid evaluation of pollution management scenarios. In the third chapter, a 2D UNet-based emulator simulates daily mean surface concentrations of NO2, O3, and PM2.5 over the contiguous U.S. at 12 km resolution. Trained on 2015–2019 EQUATES data using meteorology, emissions, and land data, the emulator achieves IOA values of up to 0.95 for NO2, 0.88 for O3, and 0.85 for PM2.5. Seasonal and city-scale evaluations v confirmed its ability to reproduce CMAQ outputs across varying conditions. The emulator was over 1000 times faster than CMAQ, enabling efficient national-scale assessments. Together, this work provides tools for emissions evaluation, air quality modeling, and environmental planning
Consent as Friction
No full textMany privacy laws rely on some version of consent to give individuals control over their data. For many reasons, consent requirements have remained ineffective: they have not afforded individuals control, and to the extent they did, individual control has proven inadequate to protect privacy values. This talk shows how consent mechanisms may manifest as friction rather than empowering users to exercise control over their data. Like sand in the gears of algorithmic machines, stringent consent requirements can undermine the viability of business practices from facial recognition to behavioral advertising. Two case studies support this argument: Biometric privacy laws in Illinois and Texas and recent developments in applying the EU’s General Data Protection Regulation. Building on these insights, this talk contends that U.S. policymakers and regulators should, and indeed can, likewise leverage consent as friction to undermine the economic viability of harmful surveillance-driven business models. This approach offers a pragmatic alternative to failed notions of user control over data, especially as democratic data governance too often remains beyond reach
Ethnic Discrimination and Heart-Focused Anxiety among Hispanic Young Adults: Effects on Anxious Arousal, Depression, and Fatigue
No full textHispanic young adults in the United States experience disproportionate mental and physical health disparities, including elevated rates of depression, anxiety, and fatigue. Perceived ethnic discrimination has been identified as a key contributor to these disparities, exacerbating stress-related symptoms and worsening overall well-being. Heart-focused anxiety, or the fear of potential negative consequences of cardiac-related symptoms, may be an additional cognitive-affective amplifier for mental and physical health symptoms. However, the independent and interactive effects of perceived ethnic discrimination and heart-focused anxiety on mental health among Hispanic young adults remain unclear. The current study sought to examine the main and interactive effects of perceived ethnic discrimination and heart-focused anxiety on general depression, anxious arousal, and fatigue severity among a sample of Hispanic young adults. Participants included 193 (83.4% female; Mage = 22.81 years, SD = 5.81) Hispanic college students who completed an online survey. Results indicated that both perceived ethnic discrimination and heart-focused anxiety were statistically significantly associated with greater general depression, anxious arousal, and fatigue severity (ps < .001-.008). Additionally, there was a statistically significant interaction effect for anxious arousal, such that perceived ethnic discrimination was associated with greater anxious arousal among individuals with higher levels of heart-focused anxiety (p = .018), but not among those with lower levels. The current findings highlight the distinct and interrelated roles of perceived ethnic discrimination and heart-focused anxiety in terms of common and often impairing mental and physical symptoms among Hispanic young adults
Forks in the Road: Globalization, Deindustrialization, and Economic Growth Pathways
No full textUtilizing a panel of 125 economies spanning from 1970 to 2019, we examine the role of manufacturing as a fundamental pillar of development in the era of global value chains (GVCs). We employ a layered clustering approach that categorizes countries based on income per capita and structural characteristics, such as the share of manufacturing, export complexity, resource dependence, productivity, and wages while maintaining consistency over time. Prior to 1990, most trajectories exhibited a progression from early industrialization to diversification, enhanced industrialization, increased export complexity, rising income levels, and subsequently to deindustrialization. However, post-1990, deindustrialization began to permeate middle- and low-income economies, with export complexity frequently increasing in the absence of deeper domestic industrial development. Two distinct manufacturing pathways are evident: one characterized by functional specialization amid moderate manufacturing levels and another exemplified by the East Asian model, which demonstrates sustained high manufacturing intensity. Resource-driven growth has led to income increases without significant structural transformation, and such growth has not enabled economies to achieve high-income status without initial industrialization. Manufacturing remains essential as a domestic foundation; therefore, policy efforts should focus on securing this base, enhancing capabilities within higher-value GVCs, and strategically investing resource revenues to bolster industrial capacity
Transracial Adoption Among Asian Youth: Transitioning Through an Integrative Identity
No full textTransracial adoption (TRA) places children across racial or national borders into non-biological families, raising complex questions about the adoptee&rsquo;s racial identity. Guided by the bicultural identity integration theory, <i>integrative racial and adoptive identity</i> is defined as a developmental process with transformative variations. Method: With a mixed-design method, this study examines how Asian adoptees and non-Asian American adoptive parents navigated their racial and cultural adjustment journeys. A small and non-representative sample (N = 21) (14 parents and seven adoptees) was recruited for the survey. Eleven participants (seven parents and four adoptees) attended an individual semi-structured interview to describe TRA needs and obstacles. Results: (1) Even though adoptees and parents were comfortable sharing their adoption experiences through social media, adoptees continued their racial identity inquiries, while parents thought of being role models. (2) Integrative findings show adoptees wanted to learn about their &ldquo;cultural socialization&rdquo; at a younger age with parental guidance and normalize &ldquo;reculturation&rdquo; as they continued exploring their racial identities through external support. Their TRA journeys engage families in a support network appreciating racial/cultural differences and experiencing identity shifts as a part of reculturation. Implications: A social work platform is needed to provide justice-oriented opportunities for adoptees to share integrative identity journeys and for parents to hear adoptees about their lived experiences. Their engagement in mutual communication will help them show appreciation for each other&rsquo;s efforts in the adjustment process
Integrated Platform for 2D Reel-to-Reel Characterization of 2G-HTS Superconductors
No full textThe large-scale production and application of REBa2Cu3O7−x (REBCO) coated conductors (CC) requires complementary characterization methods that can evaluate key superconducting properties over long lengths in a fast, reliable, scalable, and non-destructive manner. As demand for REBCO wires grows from manufacturers and end users, there is an increasing need for industrially compatible characterization approaches. However, many existing techniques remain unsuitable or insufficiently developed for long-length production due to limitations in speed, resolution, or practicality. This dissertation presents a reel-to-reel (R2R) characterization platform that integrates Scanning Raman Spectroscopy (SRS) and Machine Vision (MV) for continuous, two-dimensional analysis of REBCO tapes. The developed system enables: 1. Acquisition of two-dimensional Raman spectral maps over extended REBCO tape lengths. 2. Continuous machine vision capture to assess structural nonuniformities, surface defects, and chemical variations via color space analysis. 3. Profiling of tape curvature along the whole length. 4. Correlation of detected structural, chemical, and other variations with critical current density performance (Jc), as measured by 2D mapping at (77 K, 0 T) (Tapestar and/or R2R Scanning Hall Probe Microscopy, SHPM) or as data points at relevant fields and temperatures (B, T) using Vibrating Sample Magnetometry (VSM). This work demonstrates that residual strain, inferred from tape curvature, is proportional to the density of artificial pinning centers (APCs) and correlates directly with variations in performance Jc. Notably, the density of APCs correlates with infield retention factor across a wide range of magnetic fields and temperatures. While increased APC density shows a strong negative correlation with Jc(77 K, 0T) (C=0.98, p=0.001), it has no significant effect on Jc(4.2-20K, 0T), an important finding that suggests APC density can be further tuned to maximize in-field performance at low temperatures. By advancing practical, high-throughput methods for REBCO tape characterization, this platform offers a robust approach for industrial quality control. The integration of rapid structural assessment with established superconducting performance metrics contributes to the development of more effective screening techniques, supporting the long-length reliability of high-temperature superconductors in demanding applications
Investigating the Effects of Zinc on the Gut Microbiota Using Fluorescent Protein-Based Zn2+ Sensors
No full textThe gut microbiota makes a significant contribution to human health by strengthening the host immune system and producing essential vitamins and beneficial metabolites. In return, the host provides essential nutrients for the gut microbiota. As the second most abundant metal in the human body after iron, zinc is indispensable for biological processes across all forms of life. Zinc can only be obtained from food as it cannot be synthesized in the human body. Dietary changes, antibiotic treatment, and other factors can impact the availability of zinc. In response to changes in zinc availability, the gut microbiota employs a wide range of mechanisms to acquire and regulate zinc. The mechanisms used by the gut microbiota are not well-defined. Here, we performed sequence-based searches to propose zinc regulators, chaperones, and storage proteins in Lactobacillaceae. We focused on Lactobacillaceae because they are beneficial bacteria that are frequently affected by changes in zinc levels. We found no hits for zinc chaperone and storage proteins from sequence-based searches and identified several predicted zinc regulators for Lactobacillaceae including Zur, TroR, and ZntR. Zinc levels in the gut microbiota are tightly regulated and might vary under different conditions. Some bacteria like Escherichia coli can grow under different oxygen levels and adopt different metabolic modes depending on oxygen availability. However, the effects of varied oxygen availability on zinc uptake have not been studied. We investigated the effects of different oxygen levels on zinc accumulation in E. coli using fluorescent protein-based sensors. We utilized CreiLOVN41C, a flavin-based fluorescent protein, the ZapCY series, which are GFP-based fluorescent proteins, and inductively coupled plasma-mass spectrometry to detect and measure zinc levels in E. coli under aerobic and anaerobic conditions. Our results showed that zinc uptake in E. coli was affected by the oxygen level. Most gut bacteria are anaerobes, so GFP-based sensors are not readily applied to anaerobic bacteria. CreiLOVN41C is an oxygen-independent sensor, but it cannot be used for zinc quantification because it is intensity-based. We engineered an oxygen-independent ratiometric sensor by fusing CreiLOVN41C with miRFP670nano. This ratiometric sensor will enable zinc quantification in anaerobic organisms