An initial assessement of moral attitude dynamic model for defusing culture war tensions

[EMBARGOED UNTIL 08/01/2025] This dissertation introduces Moral Attitude Dynamic Model (MADM) for defusing conflicts tensions by incorporating the key constructs of Moral Foundation Theory into The Contingency Theory of Accommodation (Contingency Theory). MADM advances Contingency Theory by incorporating both the key conceptual constructs and methodological approaches of Moral Foundation Theory. Consequently, it allows for real-time tracking and analysis of target public's attitudes towards a certain issue as it allows for the employment of computational methods. Therefore, this model could effectively inform conflicts management and political polarization. Accordingly, MADM extends the application of Contingency Theory in the context of social controversies with a long history. Moreover, this study applies MADM on defusing the tensions of two culture issues (GM food and Abortion) as an initial assessment. Concretely, issue related tweets were scraped through academic API provided by Twitter, and issue supporters' and opponents' tweets were identified by supervised machine learning classifiers for each issue respectively. Distributed Dictionary Representation, a Natural Language Processing tool was adopted for quantify supporters' and opponents' moral stances along the enhanced contingency continuum, the key construct of MADM, and multilevel linear modeling was adopted to investigate the quantified moral stances. Accordingly, pro-GM food and pro-abortion messages were constructed based on the moral stance diagnosis results and an experiment was conducted for message and model effectiveness evaluation. The experiment results show the potential of MADM as an effective tool for conflict management. The moral reframed pro-abortion message constructed based on MADM significantly decreases the participants' anger and the affective polarization. In sum, the results suggest that MADM could be a great tool for monitoring the public's opinion, developing quick responses, and evaluating the intervention. In other words, MADM could be a great tool for mitigating polarization and for real-time conflict management in the ever-changing environment.Includes bibliographical references

Deep learning enabled materials design and characterization

[EMBARGOED UNTIL 05/01/2025] In this dissertation, deep learning methodologies are applied to innovative computational approaches for the development and characterization of materials in the material science field. The first part of the research focuses on a physics-informed machine learning workflow for virtual experimentation in the 3D printing of thermoplastics, where traditional methods are limited by complex chemical reactions and extensive design possibilities. Utilizing a dataset of 62 formulations and 216 Stress-Strain curves, this method employs dimension reduction and a novel machine learning model with physics-informed descriptors to simulate over 100,000 virtual experiment sets in under one minute, significantly enhancing the speed of material discovery. The second part improves the analysis of characterization data, specifically X-ray diffraction (XRD) patterns, by using Transformer-based models that surpass previous CNN-based models in training speed and accuracy. This segment introduces a novel data augmentation technique that simulates experimental errors and uses interpretability analysis to show how the model captures long-distance interactions between XRD peaks. It also explores the potential of transfer learning from XRD to Fourier-transform infrared spectroscopy (FTIR) data, broadening the model's applicability and improving the efficiency and accuracy of material characterization. Overall, this dissertation demonstrates how deep learning can revolutionize material science research, providing faster, more accurate tools for material development and analysis.Includes bibliographical references

The lived experience of bilateral risk-reducing mastectomy and impact on body image in young women with increased lifetime hereditary breast cancer risk

[EMBARGOED UNTIL 05/01/2025] Previvor is a term applied to a person with an identified, elevated lifetime cancer risk but who lacks a cancer diagnosis. Management strategies can be undertaken to decrease the risk of developing certain cancers. For women with a pathogenic variant that increases the predisposition for a breast cancer diagnosis, a bilateral risk-reducing mastectomy (BRRM) is the most effective cancer prevention strategy. Currently, there is a dearth of literature examining BRRM and its effects on young women. This study sought to understand the lived experience of BRRM, along with its impact on body image, in young female previvors in the first 12 months following surgery. Two qualitative methods, descriptive phenomenology and photo-elicitation, were utilized to describe the lived experience of BRRM and body image. Narrative data served as the primary data source, augmented by participant-provided visual data. A sample of 13 women were interviewed. Eight themes were found to describe how young previvors process an increased lifetime breast cancer risk, select BRRM and reconstruction methods, and express the effect of BRRM on body image. Findings provide a rich description of risk-reduction and body image outcomes in young previvors. Results from this project will be used to design future research for improving the physical and psychosocial health of this unique population.Includes bibliographical references

Replacing titanium dioxide in food products with a natural alternative made from acid whey and millet

[EMBARGOED UNTIL 05/01/2025] The increasing interest in replacing synthetic food additives with healthier, more sustainable alternatives has directed considerable attention toward titanium dioxide (TiO2), a widely used whitening agent in the food industry. This study explores the replacement of TiO2 in food products with a natural alternative made from acid whey and millet, addressing the health and environmental concerns associated with TiO2. Acid whey (AW) is a byproduct of Greek yogurt production, and it presents environmental disposal challenges because of its high mineral content and high biological oxygen demand. Simultaneously, millet, known for its high nutritional value and climate resiliency, has yet to be fully utilized in food processing. This research investigates using millet (Barnyard and Little millet) as a neutralizer and encapsulating agent for acid whey to facilitate its spray drying. Through optimization experiments, two formulations of acid whey millet (AWM) powder, Barnyard millet acid whey (BAW) and Little millet acid whey (LAW), were developed, both exhibiting excellent physio functional properties, water solubility, and particle sizes ranging from 1.18 [plus or minus] 0.02 to 1.42 [plus or minus] 0.14 [mu] m. Millet addition to AW also improved AWM powders' glass transition temperature, shape, morphology, and antioxidant activity. Chemical analysis demonstrated high lactose, minerals, and antioxidant levels in AWM powder, highlighting its potential as a functional food ingredient. A comparative analysis with TiO2 revealed comparable lightness and whiteness index in AWM, alongside superior nutritional and functional attributes. AWM proved effective as a TiO2 substitute in confectionery coatings and iron-fortified extrudates without compromising quality or safety. The study also addresses scaling up this solution from laboratory to pilot plant trials, discussing encountered challenges and insights. This research significantly contributes to discussions on sustainable food additives, offering practical solutions for safer, more environmentally conscious food practices by leveraging acid whey and millet's synergistic potential as a natural food whitening agent.Includes bibliographical references

Applications of deep learning in protein structure prediction : from complexes to intrinsically disordered proteins

[EMBARGOED UNTIL 05/01/2025] Proteins are essential biomolecules that play crucial roles in various biological processes within organisms. Their complex interactions and structures are fundamental to understanding cellular mechanisms and developing therapeutic strategies. However, traditional experimental methods like X-ray crystallography and NMR spectroscopy, despite their accuracy, are costly and time-consuming. This has prompted the exploration of computational models, particularly deep learning techniques, to predict protein structures, especially of complexes, more efficiently. This dissertation presents the development of DNCON2_Inter, DeepComplex, and Disformer. DNCON2_Inter predicts inter-chain contacts in homooligomers using deep convolutional neural networks, leveraging monomeric multiple sequence alignments (MSAs) and co-evolutionary features to enhance prediction accuracy. Using the predicted inter-chain contacts as distant restraints, quaternary structures can be produced. High precision of the inter-chain contacts leads to better quality models of the complexes. DeepComplex, a web server, extends this approach to predict inter-chain contacts and reconstruct quaternary structures of both homodimers and heterodimers. Finally, Disformer, was proposed in the prediction of intrinsically disordered proteins (IDP) which only gain structural and functional importance upon interaction with other molecules. Disformer employs a transformer-based dual graph approach combining Graph Attention Networks (GAT) and Graph Convolutional Neural Networks (GCN). It excels in predicting intrinsically disordered regions (IDRs) by leveraging both sequence-based and structure-based features for a comprehensive graph-based binary node classification. These contributions collectively enhance the predictive capabilities of protein structural analysis, providing new insights into protein interactions and disorder. This research not only advances our understanding of protein dynamics but also paves the way for future developments in the prediction and analysis of protein complexes and IDPs.Includes bibliographical references

Judicial Decision-Making in Intimate Partner Violence Cases: A Scoping Review and Critical Analysis

Family courts have increasingly made decisions in intimate partner violence (IPV) cases that extend or restrict protections for certain groups of survivors, impacting both the individuals and their family systems. Understanding how judicial decisions are made in cases involving IPV is critical to addressing systemic issues and advocating for fair, predictable outcomes for underrepresented populations. This scoping review paper identifies scholarships that inform us on how court decisions are made for cases involving IPV in the literature. Scholarships in the literature are analyzed based on the framework of intersectionality – a lens that many IPV scholars have suggested to be appropriate in revealing how structural forces reinforce social inequalities – and American Legal Realism – a legal theory that provides a useful theoretical perspective in analyzing judicial decision-makings. The analysis addresses knowledge gaps in the literature and ends by suggesting directions for future research including, an integration of the two frameworks to better understand court decisions of IPV cases.This is an original manuscript of an article published by Taylor & Francis in Family Transitions on Jan 25, 2025, available at: https://doi.org/10.1080/28375300.2025.245377

Exploring influences of sense of belonging among staff of identity centers

[EMBARGOED UNTIL 08/01/2025] The world of academia heavily focuses on a sense of belonging, research surrounding students is flourishing, and academic programs are following. Research and practice focusing on staff's sense of belonging are minimally studied. Especially given the current political climate on diversity, equity, and inclusion (DEI) education, exploring positions within this field is imperative. This study aims to explore the influences of a sense of belonging among the staff of university identity centers--an identity center is a student-centered office designated to develop identity and culturespecific content. The data for this study was collected through a demographic survey and virtual semi-structured interview with eight staff members of identity-based centers. Interview transcripts were analyzed and found to fall within four themes based on Strayhorn's (2019) and Schlossberg's (1989) theories surrounding a sense of belonging: identity, the value of mattering, flexibility, and motivation. All themes are interconnected and showcase potential opportunities for a positive sense of belonging and potential threats towards a sense of belonging, which were generated into subthemes for each original theme. Participants addressed different influences that contributed to their sense of belonging, showcasing the extremes of mental health distress to flourishing in their position. Political influences surrounding DEI policy changes on campus played a significant role in the participant's responses. These findings indicate the need for changes in current policies and practices surrounding staff environments and further research regarding staff's sense of belonging.Includes bibliographical references

Coastal bivalve parasitism and its response to anthropogenic influences : a geohistorical approach

[EMBARGOED UNTIL 05/01/2025] Parasites are common and essential parts of healthy ecosystems that influence biodiversity and trophic structure. Understanding how parasite-host dynamics have changed over time proves difficult due to the lack of body fossil record for these organisms. This thesis uses parasite-induced malformations, specifically trematode-induced pits and spionid polychaete mudblisters, to track parasitic prevalence and parasite-host dynamics over time periods often beyond traditional ecological monitoring. In the northern Adriatic Sea, we examine trematode-induced pit prevalence, aggregation, and size across two distinct time bins over the last [approx] 2ky years. Over this period prevalence decreased by an order of magnitude along with decreases in number of pits per host and pit aggregation, signaling a breakdown of this parasite-host interaction at this locality. At San Juan Island, WA we use parasitic malformations in live collected bivalves to examine parasite-host dynamics over nearly two decades. Through replicating a previous study using samples collected in 2004 we observe changes in trematode-induced pitting and mudblister prevalence over these two decades. Additionally, we see decreased parasitic prevalence among an introduced species collected in 2023 when compared to a confamilial native species indicating host selectivity among parasites in the region.Includes bibliographical references

Complexation of rhenium-186 and technetium-99m tricarbonyl cores with 1,4,7-triazacyclononane based chelators for radiopharmaceutical applications

[EMBARGOED UNTIL 05/01/2025] Technetium-99m is widely used as a Single Photon Emission Computed Tomography (SPECT) imaging radionuclide in nuclear medicine due to its favorable decay characteristics (t1/2 = 6 h, [gamma] 140 keV (89 percent)) and the low cost and widespread availability of 99Mo/99mTc generators. Technetium-99m can be combined with beta-emitting rhenium radioisotopes 186Re (t1/2 = 89 h, E[beta]max = 1.07 MeV) or 188Re (t1/2 = 17 h, E[beta]max = 2.12 MeV) as a theranostic matched pair. Metal complexes of the general formula [MI(CO)3(k3-L)]+ (M = natRe, 99mTc, 186Re, 188Re) are of particular interest for radiopharmaceutical development because of the ease of synthesis of the [MI(CO)3(OH2)3]+ precursors in which the labile water ligands can be replaced by a suitable tridentate bifunctional chelator. In particular, cyclic chelators containing a 1,4,7-triazacyclononane (TACN) ring (e.g., NOTA and NODAGA) have proven to form exceptionally stable complexes with the [MI(CO)3]+ cores. In this work, we have investigated the role of the pendant arms on TACN-based chelators in complexation of the [M(CO)3]+ core through the synthesis of novel TACN-based chelators, (radio)labeling with the [MI(CO)3]+ cores, and evaluation of the stability and hydrophilicity of the resulting radiometal complexes.Includes bibliographical references

Female sex protects cerebral arteries from mitochondrial membrane potential depolarization and cell death induced by reactive oxygen species

[EMBARGOED UNTIL 05/01/2025] Stroke, Alzheimer's disease, and traumatic brain injury exacerbate the production of reactive oxygen species (ROS), leading to apoptosis in cerebral arteries. Notably, females exhibit greater resilience to vascular damage compared to males. Mitochondrial membrane potential ([delta][psi]m) depolarization is a pivotal event in apoptosis. However, under significant depolarization, ATP synthase can reverse direction, acting as a proton pump to mitigate [delta][psi]m depolarization. Additionally, alterations in the electron transport chain function may regulate [delta][psi]m. Furthermore, plasminogen activator inhibitor-1 (PAI-1), a serine protease inhibitor present in cerebral arteries, can promote cellular resilience, although its effects on mitochondrial function have not been defined. We hypothesize that during acute oxidative stress induced by exposure to H2O2, female protection of posterior cerebral arteries (PCAs) is facilitated by enhanced reverse ATP synthase activity, augmented mitochondrial electron transport function, and PAI-1 signaling. PCAs (80 [mu]m diameter) from male and female mice (age: 4-6 months) were isolated, cannulated, and pressurized to 90 cm H2O2 at 37 degreesC. Cell death was quantified with Hoechst 33342 (1 [mu]M, labels all nuclei) and propidium iodide (2 [mu]M, labels dead nuclei), and mitochondrial membrane potential ([delta][psi]m) at rest was evaluated by JC-1 and during depolarization with H2O2 with tetramethylrhodamine methyl ester (TMRM, 10 nM). H2O2 exposure (50 min) led to significantly (P<0.05) greater smooth muscle cell death in males compared to females (30 [plus or minus] 7.4 percent vs. [approx] 7 [plus or minus] 3 percent; n=8); there was a similar trend for endothelial cell death. The ATP synthase inhibitor oligomycin (2 [mu]M) greatly augmented apoptosis in PCAs from both males and females to [approx]80 percent and eliminated differences between sexes. Consistently, H2O2 evoked a more robust depolarization of [delta][psi]m in males vs. females and oligomycin enhanced [delta][psi]m depolarization to H2O2. Oxygen consumption rate (OCR) in females was significantly higher at baseline and when exposed to H2O2, while glycolysis was not altered by exposure to H2O2. In females, PAI-1 signaling contributes to resilience against acute oxidative stress damage, whereas males exhibit greater protection in the absence of PAI-1. We conclude that cerebral vessels from female mice possess greater resilience to H2O2 -induced apoptosis than males by limiting depolarization of [delta][psi]m and though sex differences in PAI-1 signaling.Includes bibliographical references