A Bootstrap Algorithm for Testing the Equality of Phi Correlation Matrices in Text Mining

In text data analysis, researchers often use ϕ correlation matrices as inputs for network visualizations (Aruga et al., 2022; Buschken & Allenby, 2016; Lee et al., 2021). These visualizations are typically compared across groups, and differences are inferred visually. However, this approach lacks formal statistical tests to evaluate whether the correlation matrices differ significantly across groups. This dissertation introduces a parametric bootstrap algorithm for testing the equality of multiple ϕ correlation matrices across groups. The algorithm generates bootstrap samples under the null hypothesis treating observed sample statistics as population parameters. Two simulation studies assessed the algorithm’s ability to control Type I error under conditions common in text data analysis. Study 1 focused on equal correlations with equal marginals. Study 2 examined more complex cases with varying correlations and unequal marginals. The algorithm maintained nominal Type I error rates given sufficient sample sizes. This method offers a practical tool for testing group differences in word co-occurrence structures. It can be integrated into text analysis pipelines by helping detect meaningful group based differences before tasks such as network plotting

Restorative Justice in Transportation Planning: Evaluating Equity and Freeway Redress Across Reconnecting Communities Projects in Pasadena and San Diego

This report evaluates the extent to which federally funded Reconnecting Communities Pilot (RCP) projects align with restorative justice (RJ) principles, focusing on three case studies: two in Pasadena and one in San Diego. Drawing from a mixed-method approach, the research integrates a literature review of freeway-related harm, spatial analysis of displacement vulnerability, and a comparative evaluation of project merit criteria. The analysis highlights how historical infrastructure decisions disproportionately displaced low-income communities of color, producing long-term socioeconomic and environmental inequities that persist today. While federal initiatives such as RCP and Justice40 mark a significant policy shift, their effectiveness hinges on implementation.Findings from both Pasadena projects demonstrate strong alignment with community-led planning and anti-displacement strategies, though public responses revealed tensions between historical acknowledgment and present-day resistance. In contrast, San Diego’s Mend the Gap project proposes spatial reconnection through lid parks but lacks a clear implementation plan for preventing displacement–despite merit criteria emphasizing equity. Spatial analysis confirms elevated gentrification risk in surrounding areas.Across all three cases, restorative intent does not always translate into restorative outcomes. Projects that fail to incorporate enforceable anti-displacement tools, land use protections, and shared governance risk perpetuating the very inequities they seek to redress. This research underscores the need for a robust RJ framework that integrates spatial reparations with community power-building. The findings provide actionable insights for planners, policymakers, and advocates aiming to ensure that infrastructure investments produce not only physical reconnection, but also lasting equity for historically harmed communities

From tectonic stress field to surface deformation: A global analysis

The state of lithospheric stress governs geological processes and surface deformation across multiple spatial and temporal scales. At long wavelengths, it is driven by mantle flow and variations in lithospheric structure. Understanding how these stress sources shape surface deformation is key to linking deep and surface processes. Yet, challenges remain: modeling stress from structural heterogeneity is complex, surface expressions of stress are difficult to isolate, and interactions between tectonic stress and surface processes are not fully understood. This thesis addresses these challenges by (1) analyzing how structural variations influence the tectonic stress field, (2) evaluating how different stress sources affect surface features—particularly faults and rivers, and (3) examining how faults enhance erosion through stress-induced deformation. I use gravitational potential energy (GPE) contrasts and finite element modeling in spherical geometry to simulate lithospheric stress fields and compare model predictions to observations from the World Stress Map. Results show that a GPE integration depth of 100~km yields the best agreement with observed stress orientations. Models without additional imposed isostatic adjustment outperform those using isostasy assumptions. These results demonstrate the sensitivity of stress fields to lithospheric structural parameters. I further show that fault orientations generally align with the azimuth of the most compressive horizontal principal stress, hereinafter referred to as the stress direction, consistent with Anderson’s theory of faulting. River flow directions, particularly for major rivers, are also influenced by nearby fault orientations. Different stress sources affect fault patterns in distinct ways: lithospheric heterogeneity more accurately predicts normal fault orientations, while mantle flow better explains reverse fault patterns. To quantify this relationship, I introduce a new metric for mantle flow influence, which serves as a proxy for lithospheric strength. Finally, I investigate how active tectonics influence erosional processes. I show that erosional efficiency is significantly elevated within approximately 100–150~km of fault traces, especially near reverse faults and long fault segments, and decays with distance following an inverse power-law relationship. Machine learning analyses reveal that fault proximity is a stronger predictor of erosional efficiency than either precipitation or lithology. These findings indicate that active tectonics, governed by lithospheric stress, influence landscape evolution not only through uplift but also by enhancing rock damage and erodibility

Impacts of Dissolved Iron on Alkaline Water Electrolysis Cells

Dissolved iron (Fe) species are prerequisites for the most active catalyst sites for the oxygen evolution reaction in alkaline electrolytes, but the overall effects of dissolved Fe on energy-efficient advanced alkaline water electrolysis cells remain unclear. Here, we systematically control the concentration of Fe in a model zero-gap alkaline water electrolyzer to understand the interactions between Fe and high surface area catalyst coatings. Cells employing a platinum-group-metal-containing cathode and a high surface area, mixed-metal-oxide anode yielded an optimum voltage efficiency at elevated temperatures and in the presence of 6 ppm Fe, which reduced the cell voltage by ∼100 mV compared to rigorously Fe-free electrolytes. Increasing concentrations of Fe led to a systematic increase in anode activity toward the oxygen evolution reaction and a reduction in the electrochemically active surface area at both the anode and cathode. Metallic Fe was not observed to electrodeposit at cathodes which operate at overpotentials ≤120 mV, but dissolved Fe does reduce the apparent number density of sites available for hydride adsorption. These findings suggest that the energy efficiency of advanced alkaline water electrolysis systems can be improved by managing the Fe concentration in recirculating KOH electrolytes

Selective Electrochemical Reduction of CO2 to Metal Oxalates in Nonaqueous Solutions Using Trace Metal Pb on Carbon Supports Enhanced by a Tailored Microenvironment

In this work, the electroreduction of carbon dioxide (CO2) to oxalate is enabled by incorporating trace metallic lead (Pb) on carbon-based supports (CBS) with polymer overlayers. These composite materials serve as an efficient electrocatalytic system for the facile conversion and storage of CO2, a pernicious atmospheric pollutant. Results from controlled potential electrolysis experiments indicate that 1) trace metallic Pb on the ppb scale is active toward the reductive coupling of CO2 to oxalate at comparable Faradaic efficiencies to bulk metallic Pb and 2) polymer encapsulation of this trace metallic Pb leads to promotion of CO2 reduction (CO2R) selectively to metal oxalates over other products such as CO. Importantly, metal oxalates are important alternative cementitious materials and precursors for other materials’ synthesis applications. The solid products undergo rigorous spectroscopic characterization, including 13CO2 labeling experiments, to ensure the metal oxalates are in fact produced from CO2R. These findings serve as a model for leveraging microenvironment effects to enhance activity and selectivity for CO2R using trace-metal catalysts for carbon utilization and storage technologies

A Data-driven Method to Identify Wrong-Way Driving Hotspots: Assessing WWD-Prone Ramps in California District 8

Wrong-way driving (WWD) is a critical safety challenge that can rapidly lead to head-on collisions and severe injuries. Despite its relatively rare occurrence compared to other crash types, WWD incidents exhibit disproportionately high fatality and injury rates (Zhou et al., 2023). However, despite the implementation of various WWD countermeasures, transportation agencies still lack a systematic process to identify which exit ramps are at the highest risk for wrong-way entry (Zhou et al., 2018). As a result, countermeasures may not be optimally deployed at the locations most in need. Furthermore, limited data availability – such as sparse WWD incident records and lack of entry point information – significantly hinders the identification of WWD locations.This study focuses on identifying WWD-prone ramps in California’s District 8 through a statistical approach that uses California Highway Patrol (CHP) incident data. Two complementary data analyses were performed: ramp-specific methods, which tied incidents to known off-ramp origins, and non-ramp-specific methods, which attributed WWD events to probable ramps within a five-mile downstream buffer. Results highlight consistently high incident counts at ramps such as Milliken Avenue, Magnolia Avenue, and 27th Street, indicating a strong need for targeted interventions. Notably, some ramps that were less prominent in the initial ramp-specific analysis (e.g., Hidden Valley, La Sierra) emerged as major concerns in the subsequent non-ramp-specific analysis. This suggests potential underreporting or ambiguous incident records. A spatial heatmap further revealed that these ramps commonly lie in urban or suburban corridors with complex interchange designs, reinforcing previous findings (Chang et al., 2024) that geometric layout and visual cues are key WWD risk factors.Drawing on these insights, the study proposes a systematic prioritization framework for mitigating WWD hotspots. Policy recommendations include enhanced ramp signage, wrong-way detection systems, and improved CHP data labeling protocols to reduce the manual burden of text-log analysis. Taken together, this work underscores the value of a multi-faceted, data-driven strategy for addressing WWD. While total elimination of wrong-way incidents remains challenging, the methods and findings presented here provide a foundation for more proactive, efficient, and scalable WWD prevention efforts in California and beyond

Spatial analysis of mitochondrial gene expression reveals dynamic translation hubs and remodeling in stress

Protein- and RNA-rich bodies contribute to the spatial organization of gene expression in the cell and are also sites of quality control critical to cell fitness. In most eukaryotes, mitochondria harbor their own genome, and all steps of mitochondrial gene expression co-occur within a single compartment-the matrix. Here, we report that processed mitochondrial RNAs are consolidated into micrometer-scale translation hubs distal to mitochondrial DNA transcription and RNA processing sites in human cells. We find that, during stress, mitochondrial messenger and ribosomal RNA are sequestered in mesoscale bodies containing mitoribosome components, concurrent with suppression of active translation. Stress bodies are triggered by proteotoxic stress downstream of double-stranded RNA accumulation in cells lacking unwinding activity of the highly conserved helicase SUPV3L1/SUV3. We propose that the spatial organization of nascent polypeptide synthesis into discrete domains serves to throttle the flow of genetic information to support recovery of mitochondrial quality control

Multiple kinesins speed up cargo transport in crowded environments by sharing load

Kinesin motors transport cargoes along microtubules inside of cells. Although it is well known that the cargoes are typically carried by multiple kinesins and that the more motors used, the further the cargoes travel, it has been challenging to determine the number of motors moving a cargo and any instant. Further, there is no unified statement on the relationship between cargo velocity and motor number, especially in the presence of a very crowded cytoplasmic environment. Here, we use a non-invasive method to quantify instantaneous motor number, and use it to investigate the effects of crowded environments on cargo motion when it is carried by multiple kinesins. Our experiments reveal that the velocity of the cargo depends on the number of motors on the cargo and the size of the crowders in crowded environments. Our finding suggests that kinesin tension plays a role in collective motion, which has been confirmed through stochastic kinesin simulations. Overall, our study demonstrates the broad applicability of the non-invasive method to determine engaged motor numbers and sheds light on the intriguing interplay between macromolecular crowding, kinesin tension, and kinesin-mediated cargo transport