Vessels of Spirituality: Merging Faith and Form

According to traditional Islamic teachings, natural materials like frankincense, black sesame seeds, and sidr (jujube) leaves are valuable both physically and spiritually. Historically, they have been used for healing and purification. Nowadays, influenced by contemporary science, people tend to overlook their metaphysical value, focusing on their medicinal uses. Similarly, Muslims assign spiritual qualities to the Muqatta’at, the disconnected letters that preface several surahs of the Holy Quran, believing them to contain sacred power. In both of these cases, the material leads to the spiritual. Through material experimentation, informed by religious texts, my thesis combines revered materials with sacred letter forms in unconventional ways, offering a conceptual design framework where material spirituality inspires poetic physicality. By bridging the ancient and the modern, the spiritual and the physical, this work inspires a renewed appreciation of Islamic teachings and material culture

Indiana Prison Writers Workshop: The Power of Group Cohesion and Creative Expression among Incarcerated Individuals

Objective: The present study describes the development of the Indiana Prison Writers Workshop (IPWW), a creative writing workshop, based in group theory and designed for incarcerated settings. Methods: Quantitative evaluation data from IPWW workshops conducted from 2023-2024 were analyzed using IBM SPSS V. 29. Prior to the workshop, 149 men responded to questions on class expectations and goals, and 115 men responded at workshop conclusion. Open-ended qualitative responses from post-workshop data were analyzed using thematic analysis. Results: Quantitative data demonstrates the effectiveness of IPWW in teaching writing skills and reflects participants’ agreement that the workshops provide opportunities to share their work and receive feedback from peers and the facilitator. Five themes emerged from the qualitative data: 1) self-expression, 2) skill development, 3) self-reflection, 4) perspective, and 5) therapeutic. Conclusions: We discuss how these results influence group cohesion among incarcerated men and explore implications for future research and IPWW program development

The Accuracy of Tooth Movement with Artificial Intelligence-Based Clear Aligners

Background: Artificial Intelligence (AI) and machine learning (ML) may offer innovative solutions for the virtual planning of clear aligner therapy, enhancing precision and efficiency in orthodontic treatment. The purpose of this study is to assess the accuracy and reliability of an AI-based clear aligner system\u27s virtual treatment simulations (predictions). Purpose: The primary objective of this observational clinical study is to assess the accuracy of a virtual treatment plan utilizing ML algorithms by comparing the predicted tooth movements with the actual clinical movements at three and six months. The secondary objective is to determine whether the use of cone beam computed tomography and machine learning algorithms accurately predicts alveolar bone defects at six months of treatment. Methods: The models of the actual Crown-Only positions at three months and the Crown-Only and Crown-Root positions at six months were superimposed on the digital images of predicted tooth positions using Geomagic Control X Software. The mean absolute difference (MAD), root mean square (RMS), and percent within tolerance between the models was calculated to examine how well the software predicted tooth movements. Descriptive analysis was used to estimate the presence of bone defects. Results: Nine patients were recruited for this study, but only six completed and were included in the analyses, yielding a total of 12 arches. The mean absolute difference and root mean square were significantly higher for 6m Crown-Only than Crown-Root models. The percent within tolerance was higher at three months than six months for the Crown-Only models (71% vs. 63%), and higher for the Crown-Only models compared to the Crown-Root models at 6m (63% vs. 57%). The ML software predicted 14 instances of bone defects (8%) out of 168 sites. ML software predicted defects in 11 sites where none were present clinically (7%) and failed to predict defects in 3 sites where they were observed clinically (2%). Conclusions: AI-based clear aligners predicted tooth movements with a slight improvement in accuracy when compared to traditional clear aligners that do not utilize this technology when developing a virtual treatment plan. The predictions using Crown-Root model superimpositions were less accurate than those using the Crown-Only model superimpositions at six months. ML software demonstrated a tendency to overestimate the presence of bone defects

Men\u27s Perceptions of Autonomous Reproductive Choices

INTRODUCTION: Reproductive coercion (RC) impacts approximately 10.1 million women in he U.S. It is a specific form of intimate partner violence (IPV) that refers to behaviors from a partner through the use of fear or control that undermines the ability to make autonomous decisions regarding reproductive health. Because homicide is the leading cause of death among pregnant women in the U.S., the consequences of leaving RC unaddressed underscore the need for additional research to focus on obtaining a clearer definition of RC and correlates of this form of violence. Moreover, despite being frequently cited as a necessary research direction, studies have seldom assessed men’s perceptions of RC. METHODS: This study developed a vignette-based measure of perceptions of RC through expert panels and cognitive interviews. Once the measure was developed, a national sample of heterosexual men ages 18-40 using the online market research platform, Prime Panels (n=323) was used to examine men’s perceptions of RC and how those perceptions may differ by known predictors of other forms of sexual violence via a cross-sectional survey. RESULTS: The developed vignette measure showed strong psychometric properties as evidenced by an Exploratory Factor Analysis and Cronbach’s alpha coefficients. Two multiple linear regressions were used to examine relationships between variables and how changes in values of rape myth acceptance, sexual double standards, gender role norms and hostile sexism collectively explain the change in men’s perceptions of reproductive coercion while accounting for relevant control variables. Rape myth acceptance and rigid gender role norms were significantly associated with men’s perceptions of pregnancy coercion. Rape myth acceptance and rigid gender role norms were also significantly associated with men’s perceptions of condom manipulation. CONCLUSION: These findings suggest that condom manipulation and pregnancy coercion are distinct constructs, although they both fall under reproductive coercion. Men’s adherence to rape myths and rigid gender roles should be qualitatively explored further to gain a deeper understanding of how this may shape their perceptions of this specific form of violence

Development and Application of Xerogel Insulated Glazing for Enhanced Building Insulation

The research and development of new building materials and techniques for energy saving insulation is a main focus in the building sector. In recent years, the application of aerogels as insulating components of window glazing has shown promising results, however, due to the nature of the synthesis of these materials, they remain an impractical solution. The aim of this research is to address the growing demand for energy-efficient building solutions by leveraging the unique properties of xerogels to improve thermal performance and reduce heat transfer in insulated glass units. This research will address the growing demand for energy efficient window insulation by integrating a transparent silica xerogel into a traditional single, double, and triple pane insulated glazing, significantly lowering thermal transfer through windows and increasing energy efficiency

HAFNIUM OXIDE-BASED NANOHETEROSTRUCTURES FOR CATALYTIC RADIOSENSITIZATION AND ENHANCED X-RAY RADIOTHERAPY

Orthovoltage X-ray beams are attractive for surface and intra-operative radiotherapy. Yet, their clinical utility is constrained by rapid attenuation and the limited dose that can be delivered without harming healthy tissue. High-Z hafnium oxide (HfO2) nanoparticles can boost local energy deposition through the photoelectric effect, while catalytic surface defects accelerate water radiolysis. Harnessing both mechanisms in a single nano-heterostructure could enable potent radiosensitization at diagnostic-range energies. This thesis develops and evaluates HfO2-based nanoheterostructures, both bare and Au-decorated, as catalytic radiosensitizers. Two types of HfO2 were evaluated, one was synthesized following a specific route and the other commercially available. Afterward, each HfO2 was decorated with Au nanoparticles via a wet-chemical route. Crystallite size, phase, morphology, Au loading, and surface chemistry were investigated by XRD, TEM and XPS. Cat- alytic radiosensitization was assessed by monitoring pseudo–first-order degradation of methylene blue under 70kV, 100kV, 150kV and 225kV X-rays, varying nanoparticle concentrations (0.10, 0.25, 0.50, 0.75, and 1 mg mL−1). The hydrothermally synthesized HfO2 rose the rate constant k by up to 0.110 min−1 and delivering a 43% enhancement at 225 kV; even at 70 kV it achieved a 30% gain. Au decoration passivated active sites on this support, adding no more than 6%. In contrast, the commercial powder showed minimal benefit, \u3c 10 %, unless augmented with Au, which restored activity to 19 % at the lowest energy tested. Performance correlates with lattice disorder and surface defect chemistry rather than Au loading alone. By tailoring synthesis to maximize oxygen-vacancy density while controlling noble-metal coverage, catalytic dose amplification approaching 40 % can be achieved across the entire 70 kV to 225 kV window. Together, these insights set the stage for HfO2 nanomaterials that maximize therapeutic gain at low kilovoltage energies with minimal collateral toxicity

Climate change-induced shifts in Mediterranean fungal fruiting phenology and productivity

We used a 29-year dataset of mushroom fruiting from the Pinar Grande forest in northern Spain to investigate the effects of climate change on the phenology, productivity, and diversity of mycorrhizal and saprotrophic mushrooms. We investigated the long-term trends in fruiting season length, yield (by count, total weight, and average weight), and genus richness. Additionally, we identified associations between monthly temperature and monthly precipitation with these fungal responses across functional groups: mycorrhizal, saprotrophic, litter-decaying saprotrophic, and wood-decaying saprotrophic mushrooms, and the economically-important edible genera Boletus and Lactarius. We found that autumnal season length in the Pinar Grande has shortened over time across functional groups, apart from wood-decaying saprotrophs. Litter-decaying saprotroph genus richness trended slightly upwards over the course of the study period. Higher precipitation July through September was generally a predictor of longer fruiting seasons and higher yields across functional groups, while high temperatures during these times were generally negatively associated with mycorrhizal season length and productivity, and positively associated with saprotroph season length and productivity. The dependence of mushroom fruiting on weather depended on their functional group: the fruiting responses of mycorrhizal fungi and litter-decaying saprotrophs were more closely tied to weather than that of wood-decaying saprotrophs. We conclude that increasing temperatures and decreasing precipitation alter mushroom fruiting in the Mediterranean region, particularly through the declining length of the fruiting season across functional groups and decreasing productivity of edible fungi, which carries potential consequences for both local forest ecosystems and myco-economies

Sunlight, Veiled

Sunlight, Veiled is a narrative short film exploring themes of displacement, class, and identity through the lens of an Iranian intern navigating a morally ambiguous company party in the United States. This written component traces the evolution of the project from development through post-production, while reflecting on the personal and political frameworks that shaped the creative process. Through cinematic references, cultural analysis, and production insight, the paper aims to contextualize the film within a diasporic experience and a growing awareness of social power dynamics. It also reflects on the challenges of filmmaking as an outsider, where self-doubt, cultural translation, and shifting expectations constantly redefine what it means to tell a relatable story

Food Waste Renaissance: From the Table, for the Table

What if waste could be seen as a valuable resource rather than a burden? Food Waste Renaissance (FWR) explores innovative ways to transform excess food and byproducts into sustainable design materials. In Qatar, where food waste constitutes approximately 60% of urban waste, FWR promotes a shift in perception rather than attempting to resolve large-scale waste management issues. By fostering a culture where surplus becomes a resource, it inspires individuals, designers, and communities to embrace and contribute to a circular economy. FWR examines rice and date byproducts as biodegradable raw materials for lamps, bringing material from the table back to the table. Their translucency, texture, and organic unpredictability lend themselves to a unique outcome, demonstrating how today’s waste can become tomorrow’s sustainable design solutions

Cluster Modified Nanopore for Protein Post-Translational Modification Detection

The precise and sensitive detection of protein post-translational modifications (PTMs), particularly phosphorylation, is critical for advancing our understanding of cellular signaling and disease pathology. In this thesis, we present a nanopore-based biosensing platform enhanced by cluster modifications, offering novel capabilities for the single-molecule analysis of phosphorylated peptides. The introductory chapter outlines the principles of nanopore sensing and its relevance as a next generation biosensing technology. The second chapter explores the use of nanoparticle-assisted nanopores for detecting ovarian cancer peptide biomarkers, demonstrating the method’s capability to discriminate between cysteine-containing peptide variants from clinically important proteins such as LRG-1. Building on this, the third chapter presents a detailed study on the discrimination of isomeric phosphorylated peptides derived from the human insulin receptor. A cluster-modified nanopore platform enabled accurate identification of phosphorylation states at the single-molecule level. To enhance the classification of nanopore signals, a Gaussian Mixture Model (GMM)-based machine learning pipeline was developed and optimized specifically for the complex signal profiles produced by the cluster-modified nanopore. The fourth chapter is dedicated to the design and optimization of the GMM algorithm, tailored to capture the multi-modal characteristics of the nanopore signal distributions. The final chapter examines the interaction of titanium dioxide (TiO₂) nanoparticles with phosphonate ligands in the nanopore environment, offering insight into the chemical challenges and opportunities in designing phosphonate-specific sensing platforms. Altogether, this work establishes an integrated strategy for high precision phosphoproteomic sensing using modified nanopores and machine learning, demonstrating the potential of this technology for both research and clinical diagnostics