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Gender, Resistance and Resilience: Reckoning Trauma and Destruction Through Iraqi Artscapes
No full textThis dissertation explores the intersections of gender, resistance, and resilience within Iraqi visual culture, tracing the transformative role of women artists from the 1970s to the present. It examines how Iraqi art, especially by women, has served as a medium of dissent, identity formation, and historical memory amid war, occupation, and displacement. Through a feminist rhetorical lens, the study interrogates the ways in which women’s bodies, voices, and artworks have navigated and challenged patriarchal, colonial, and state-sponsored narratives. Drawing on ethnographic research, including interviews with artists both in Iraq and the diaspora, this project considers how transnational feminist visual rhetoric has redefined the image of Iraqi womanhood - from national symbol to active agent of sociopolitical change. This research further analyzes how grassroots movements like the 2019 Tishreen protests have utilized visual expression to reclaim public space and assert collective identity. Ultimately, this dissertation contends that contemporary Iraqi art is not merely reflective of trauma but is an act of resilience and reimagination, offering new ways of seeing and shaping post-conflict Iraqi society.Release after 05/01/202
Educating Anesthesia Providers on Perioperative Ketamine Administration To Decrease Postoperative Opioid Intake
No full textPurpose: The purpose of this DNP project was to increase anesthesia providers’ knowledge ofthe benefits of perioperative ketamine, specifically for patients with a history of opioid use.
Background: The opioid epidemic has highlighted the need for alternative pain managementstrategies, particularly in the perioperative setting, where anesthesia providers play a critical role
in managing surgical pain. Patients with a history of opioid use often require high doses of opioids and are at risk of inadequate surgical analgesia (Bordi, 2023). Ketamine, an N-Methyl-D-
Aspartate (NMDA) receptor antagonist, has been demonstrated to be effective in reducing perioperative opioid requirements for this patient population (Rathmell & Dahan, 2021).
Methods: An educational session was designed to assess and improve anesthesia providers’understanding of perioperative ketamine. Pre- and post-surveys were administered to evaluate
changes in knowledge, focusing on ketamine’s efficacy, safety, and potential for reducing opioid
use in surgical patients with opioid histories.
Results: The results demonstrated that the educational session led to a significant increase inanesthesia providers' knowledge and confidence in using ketamine for patients with a history of
opioid use. The educational session was effective in enhancing providers' understanding of
ketamine’s role in multimodal analgesia and reducing opioid consumption.
Conclusions: This project highlights the effectiveness of an educational intervention inimproving anesthesia providers’ knowledge of perioperative ketamine. However, a lack of
consensus on ideal dosing regimens was identified, suggesting a critical area for future research.
Further studies should investigate the impact of increased knowledge on practice change, such as
the frequency of ketamine use and retention of knowledge over time
Androgen-Induced WNT Signaling in Prostate Stromal Cells: Implications for Stromal-Epithelial Crosstalk and Prostate Homeostasis
No full textBackground: WNT signaling is crucial for prostate tissue homeostasis, regulating cell proliferation, differentiation, and function. Its dysregulation is linked to prostate cancer and benign prostatic hyperplasia, yet the specific role of stromal WNT signaling in prostate development and disease remains unclear. Understanding how stromal WNT influences epithelial cells and interacts with other pathways is key for identifying potential therapeutic targets.
Approach: Differentiated and undifferentiated human prostate stromal cells were cultured and assessed for WNT signaling activity upon R1881 induction using qPCR and TaqMan™ WNT pathway arrays. Expression of WNT ligands, receptors, and inhibitors was validated by western blotting. Functional assays using recombinant WNT proteins (WNT3A, WNT7B) were conducted on basal epithelial cells to assess downstream canonical and non-canonical signaling. FZD receptor function was evaluated using shRNA-mediated knockdown in epithelial cells.
Results: We found that WNT5A, WNT2, and WNT4 were the most abundant WNT ligands in benign prostate fibroblasts, smooth muscle cells, and basal epithelial cells, respectively. Androgen stimulation upregulated WNT3A transcription in stromal cells but led to reduced protein levels, suggesting post-transcriptional regulation. FZD10 was highly expressed in prostate cancer cells, implicating it as a potential mediator of tumor associated WNT signaling. Recombinant WNT treatment revealed context-dependent epithelial responses, favoring non-canonical signaling and β-catenin degradation.
Conclusions: This study reveals cell type–specific expression and regulation of WNT ligands and receptors in the prostate that supports epithelial quiescence and tissue homeostasis. Disruptions to this balance may contribute to prostate cancer progression and represent potential targets for future therapeutic strategies
Development of txci-CAB as a New Single-cell Approach to Study Chromatin Modifications and Accessibility Across the Genome
No full textUnderstanding the epigenomic landscape of single cells is critical for uncovering the regulatorymechanisms that govern cell identity, differentiation, and function. Traditional chromatin
profiling methods often measure a single modality per assay, limiting the ability to directly
capture the interplay between chromatin accessibility and histone modifications. To overcome
this limitation, we developed txci-CAB (10x-compatible combinatorial indexing of CUT&Tag
and ATAC both) by combining combinatorial indexing with a droplet-based microfluidic system.
In this thesis, we work on systematic optimization of ATAC-seq and CUT&Tag protocols in
order to integrate them within the same workflow to simultaneously profile accessible chromatin
states as well as specific modifications in individual cells. The txci-CAB protocol incorporates
Tn5-based combinatorial barcoding for chromatin accessibility followed by pA-Tn5-guided
CUT&Tag for histone modifications.
Although several multimodal single-cell sequencing techniques exist, txci-CAB is designed to
enhance scalability, sensitivity and overall convenience of use, both in terms of input reagents
and protocol workflow. Our approach also emphasizes increased library complexity while
maintaining robustness and reproducibility. Notably, we observed higher estimated complexity in
our bulk datasets, demonstrating the method's effectiveness in simultaneously capturing two
chromatin modalities at single-cell resolution
Eutectic and Peritectic Equilibria in Coherent Binary Alloys
No full textPhase equilibria in a coherent binary alloy for the eutectic and peritectic systems are ana lyzed in this study to construct a theoretical model that will provide conditions for three-phase equilibrium in the presence of coherency stress between the solid phases. Our analysis employs simple quadratic functions for the Gibbs energy for individual phases, considering the solid phases to be temperature-independent. To facilitate an analytical solution, we used simplified assumptions about the system, explicitly considering an infinite volume occupied by three phases and the solid phases being isotropic and linearly elastic. We use a mathematical optimization method, Lagrange multiplier, to minimize the functions of Gibbs free energy subject to the constraints of volume fractions and phase compositions that satisfy the equilibrium conditions. This theoretical study demonstrates the effect of coherency stress on invariant points of phase diagrams, including a liquid leveraging the original Larche-Cahn formulation to evaluate the impact of coherency stress on eutectic and peritectic points in binary alloys. The common tangent construction is not applicable in the presence of strain energy between the solids, and the Gibbs phase rule no longer holds. Our findings demonstrated that coherency stress has distinct consequences on the eutectic and peritectic equilibria due to the difference in compositions between one solid and liquid phase and the difference in the melting points of the solid phases; therefore, instead of forming the three-phase region, usual to eutectic equilibria, a two-phase region with one solid and liquid becomes more dominant in the peritectic equilibria
Using LiDAR Remote Sensing to Evaluate and Improve the Retrieval of Snow Depth, Leaf Area Index, and Land Cover Types for Hydrometeorological Studies
No full textRecent NASA satellite missions such as the Ice Cloud and Land Elevation Satellite version 2 (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI) have been deployed to survey the Earth’s surface with mission goals of monitoring changes in glacier ice, sea ice, and vegetation for ICESat-2 and retrieval of 3-D structure of mid-latitude and tropical canopies globally for GEDI. Both instruments have provided the community with unprecedented high-resolution active remote sensing measurements of variables relating to processes in the water cycle. These advancements in spaceborne lidar technology motivate the works performed in this dissertation that demonstrate the importance of using these instruments for the retrieval of hydrometeorological variables and provide motivation for future spaceborne lidar missions. Mitchell et al. (2025a) evaluated snow depths retrieved from ICESat-2 multiple lidar scattering measurements, a new and novel technique developed by Y. Hu et al. (2022) and Lu et al. (2022). Snow depths from ICESat-2 are compared to the in-situ measurement – derived University of Arizona (UA) product for two distinct regions of the contiguous U.S. (CONUS): the Mountain West (complex terrain) and the Great Lakes (homogeneous terrain). Biases between the snow products are co-located with several terrestrial datasets (i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), GEDI, ICESat-2, and USGS LANDFIRE) and then evaluated in terms of the time of snow season (December – April) and snow density to understand the performance of the retrieval. The retrieval performance performed well overall, but results showed the performance decreased with increasingly complex terrain and in the presence of tall canopies. Additionally, the retrieval’s performance decreased later into the snow season and with higher snow densities. The findings provided insights into future corrections that can be made to the retrieval in future studies.
Mitchell et al. (2025b) co-located GEDI spaceborne lidar canopy measurements and snow depths from UA with MODIS LAI and land cover (LC) products over the CONUS for a two-year period (2019-2021) to address the questions of if the underestimation of the MODIS LAI data for evergreen forest are due to deficiencies related to the misclassification of the input LC data or the LAI retrieval itself? Comparisons between GEDI plant area index (PAI) and MODIS LAI highlighted the MODIS retrieval deficiencies in evergreen forests, where the median GEDI PAI and MODIS LAI winter/summer ratios are 0.87 and 0.29 respectively. The sensitivity of LAI to snow cover is highest in evergreen forests where LC analyses also demonstrate the highest potential for misclassified pixels according to the International Geosphere Biosphere-Programme LC classification using GEDI canopy metrics. Corrections to wintertime LAI using the winter/summer PAI ratios are applied to tall forest LC types and showed the greatest improvements over evergreen needleleaf forest. Finally, a decision tree approach leveraging several GEDI canopy metrics showed potential to reclassify the MODIS-misclassified LC pixels and demonstrate the advantage of leveraging active spaceborne lidar measurements to improve passive remote sensing data.
Following Mitchell et al. (2025b), corrections are made to MODIS LAI prescribed to the Community Land Model version 5 (CLM5.0) for evergreen trees in the third study, to investigate the impact of using LAI datasets improved by spaceborne lidar measurements on land modeling. The findings show promising results in the improvement of the representation of LAI for evergreen throughout the year. In boreal evergreen forest, changes to the LAI substantially impacted snowpack, evaporation, and runoff by shifting the seasonal cycles by a month. For tropical evergreen forest, the largest changes were seen in wet season partitioning of evaporation, but overall changes were relatively small . These studies highlight the need for continued improvement of the retrieval of hydrometeorological properties from spaceborne lidar and the importance of continuing future spaceborne lidar missions with new advancements in lidar technology
Beyond the Checklist: Healing, Connection, and Capacity-Building Through Digital Preservation Peer Assessment: A white paper prepared for the Institute of Museum and Library Services for the Digital POWRR Peer Assessment Program
No full textWhite paper. Companion case studies available at: http://hdl.handle.net/10150/677916.This white paper documents the development, implementation, and outcomes of the Digital POWRR Peer Assessment Program (2021–2025), a cohort-based professional development initiative focused on building digital preservation capacity at under-resourced cultural heritage organizations. Funded by the Institute of Museum and Library Services (IMLS), the program combined self-assessment tools, peer mentorship, and community-informed learning to support 36 participants across two phases. The report highlights key design elements—including emotional safety, reflective goal-setting, and peer validation—and introduces Navigating Uncertainty: A Human-Centered Assessment Compass for Digital Preservation Practitioners, a new evaluative framework shaped by participant experiences. Drawing on participant feedback, mentor insights, and external evaluation, the paper offers recommendations for funders, administrators, and future implementers seeking to cultivate inclusive, emotionally sustainable models of digital stewardship. A companion volume of participant-authored case studies illustrates how digital preservation goals were translated into institutional action across a wide range of contexts.Institute of Museum and Library ServicesThis item from the Library Presentations and Publications collection is made available by the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Mapping and Developing Digital Competence of Second and Foreign Language K-12 Teachers and University Instuctors: A Collaborative Teacher Professional Development Series
No full textThis mixed-method study focused on the collaboration of a group of second and foreignlanguage K-12 teachers and university instructors in developing their digital competence
as language educators. Upon the completion of a survey to measure their digital
competence as educators, participants were invited to form a collaborative language
teachers professional development series, an organically-created grassroots initiative
with no group leaders or hierarchical structures among the participants. This series
provided a platform for these educators to collaborate with each other, engage in joint
activities, and share their expertise to enhance each other’s digital competence.
Initially, the quantitative findings obtained via surveys revealed that digital
competence of second and foreign language K-12 teachers and university instructors is
at the usage level. In other words, they integrate some educational technologies into
their language teaching settings. However, many do not analyze and evaluate the
effectiveness of technological tools, and do not collaborate with coworkers to share
expertise. To address this problem discovered in the quantitative findings, a data-driven
approach was embraced to initiate a collaborative professional development series for
second and foreign language K-12 teachers and university instructors. At the end of the
series, qualitative findings revealed that educators emphasize knowledge sharing, skill
development, positive experiences, curriculum development, and the professional
growth aspects of this collaboration. They recommend fostering further connections
through coordinated engagement among participants and enhancing learning
experiences through increased interaction. Finally, educators reported growth through collaborative learning, increased readiness in integrating technological tools, improved
evaluation of tools through peer interaction, growth through new tools, and raised
awareness.
The implication of this study is important. Integration of technologies is an issue
many educational institutions need to deal with, and many of these institutions do not
have funding to cover the costs. The overall data indicates that Collaborative Teachers
Professional Development Series is a low-cost, non-hierarchical alternative to traditional
teacher education programs. It evens the playing field for all participants, as the series
does not involve work supervisors, school principals, or employers. This provides a safe
space to reduce the element of fear in technologies, explore new educational
technologies, and shift attitudes toward a confident “Yes, I can do it, too!”.Release after 07/23/202
High-Dimensional Spatial-Temporal Data Analytics via Knowledge-Informed and Interpretable Decomposition
No full textOver the past decade, rapid advancements in sensing and data storage technologies have dramatically increased the availability and scale of spatial-temporal (ST) data, offering new opportunities while presenting significant challenges. ST data, acquired from diverse sources, often exhibit complex patterns that can be decomposed into several interpretable components: (i) a global component remaining stable, (ii) a locally distinct feature component reflecting system-specific variations, and (iii) a random noise component accounting for unpredictable fluctuations.
These decomposition principles are demonstrated across multiple application domains. In water distribution systems (WDSs), for example, pipeline bursts cause abrupt deviations in pressure that differ significantly from normal operating conditions. To detect such anomalies, an ST decomposition model is proposed that decomposes hydraulic measurements into a regular consumption component, a noise component, and a burst-induced anomaly component. Domain-specific knowledge, such as expected pressure behavior under normal and fault conditions, is integrated through information fusion to guide the decomposition, enhancing detection accuracy and robustness in real-world scenarios.
In surveillance systems, the objective is to identify moving foreground objects, such as pedestrians and vehicles, from surveillance video frames. To achieve this, a foreground detection model is proposed that decomposes video frames into background, foreground, and noise components, each regularized by distinct ST properties. For instance, static backgrounds under fixed cameras, continuously moving foreground objects, and random noise are explicitly modeled based on their characteristics, leading to improved detection effectiveness without the need for labeled data.
In structural health monitoring (SHM), data from wireless sensor networks (WSNs) deployed on infrastructure systems frequently suffer from missing values due to sensor faults or battery life constraints, compromising monitoring reliability. To address this issue, a graph-regularized decomposition method is proposed that models the spatial relationships between sensors based on their dynamic behavior, as captured by structural mode shapes. In this framework, edge weights in the graph represent inter-sensor similarity derived from mode shape correlation, allowing the imputation of missing data using only structurally relevant sensors. This targeted approach avoids interference from unrelated data and significantly enhances the missing data imputation performance and robustness of SHM systems.Release after 05/01/203
LILY LIVING WITH TYPE 1 DIABETES
No full text"Lily Living with Type 1 Diabetes" is an illustrated narrative written to explore the effects of Type 1 Diabetes on puberty from the perspective of a middle school girl. She faces normal challenges such as making friends, and fitting in, but also has to grapple with her blood sugar and blood sugar changes during onset of her menstrual cycle. Type 1 Diabetes (T1D) diagnosis, especially in children, turns a patient's world upside down. For families, it can be difficult to make the necessary adjustments to diet and lifestyle for management, and oftentimes the child is forced to become responsible for all of the nuances of their disease. Because dietary and lifestyle changes can be difficult, I wanted to emphasize the positive parts of growth and development. Through the creation of a plot, a relatable female protagonist and complimentary illustrations, I share the highs and lows (literally and figuratively) of managing a new T1D diagnosis between the ages of 10-14. I want to use this narrative to open a dialogue for children who are struggling to manage the changes in their diabetes diagnosis after puberty. I hope this story is a resource of girls experiencing body changes such as their menstrual cycle and I want to empower these children to take pride and joy in their bodies and to celebrate their differences