Open Theses and Dissertations
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Item Open Access Three-Dimensional Building Reconstruction from ALS Point Clouds(2024-10-04) Yang, Hongxin; Wang, Ruisheng; Wang, Xin; Hassan, Quazi Khalid; Yang, Hongzhou; Cheng, Yufeng(Frank); Yang, BishengReconstructing buildings from Light Detection and Ranging (LiDAR) point clouds obtained from aerial perspectives is of significant importance in the domain of photogrammetry. Given that the experimental dataset, Building3D, lacks sufficient corner points and exhibits point cloud sparsity among other challenges, point cloud completion (PCC) techniques, a branch of reconstruction, are employed to complete the building facade information. Due to the high demand for labeled data and the associated high cost of manual annotations, Self- Supervised Learning (SSL) methods for three-dimensional (3D) point clouds have garnered considerable attention from scholars. However, existing methods commonly use a standard Transformer backbone, result- ing in quadratic time complexity. To overcome these limitations, an innovative masked linear autoencoder framework is proposed. Due to the storage requirements—approximately 400:4:1 for point cloud, mesh, and wireframe formats, respectively, wireframe models have recently garnered considerable attention in the field of remote sensing. Despite some early explorations into constructing wireframe models, numerous challenges persist. This thesis revisits 3D building wireframe reconstruction from a SSL perspective, with the aim of alleviating or even addressing these existing difficulties. A two-stage Self-supervised (SS) pretraining architecture is proposed to generate wireframe models. Initially, it utilizes a SSL-based pretraining framework that incorporates a linear self-attention mechanism (SAM) to generate point-wise features. Subsequently, corner detection and edge prediction modules are employed to classify and regress the coordinates of corner points and to determine optimal edge selections, respectively. To address the issue of insufficient corner points, a SSL-based pretraining method for 3D wireframe reconstruction, guided by an edge point regression module, is proposed. The parameters of the wireframe’s edges—including edge length, direction vector, and direction offset—are regressed under the guidance of the edge point regression module. To enhance the clustering of roof wireframe vertices, an efficient approach based on a multiclass TWin Support Vector Machine (TWSVM) framework is proposed. This framework aims to simplify the model by effectively clustering roof wireframe vertices.Item Open Access Anti-Müllerian Hormone & Cardiovascular Risk in Males with Chronic Kidney Disease(2024-10-02) Larsen, Nicole; Dumanski, Sandra; Foong, Shu; Tyrone, HarrisonCardiovascular disease (CVD) is the leading cause of death globally and individuals living with chronic kidney disease (CKD) have an exceptionally high cardiovascular risk. Males living with CKD experience a disproportionately high risk of CVD mortality compared to females living with CKD. Reduced anti-Müllerian hormone (AMH), a hormone involved in sex differentiation and fertility, has been previously associated with CVD risk in healthy males and females, as well as in females living with CKD. However, whether AMH is linked to CVD in the high-risk population of males living with CKD is yet unknown. The aim of this exploratory cross-sectional study was to estimate the association between AMH and arterial stiffness, a validated predictor of CVD, in males living with CKD. Self-identified adult male individuals were recruited from Nephrology clinics in Calgary, Alberta, Canada. Individuals were included if they had a diagnosis of CKD (i.e. kidney damage or estimated glomerular filtration rate <60 ml/min/1.73 m2 for >3 months) and exclusion criteria included: 1) history of a major cardiovascular event, 2) history of any medical condition known to impact testicular function, and 3) current use of exogenous hormone therapy. Participant demographic information, medical history, physical examination, and laboratory data were collected alongside serum AMH levels, measured with a validated immunoassay. Using standardized protocols, pulse wave velocity (PWV) and aortic augmentation index (AIx) were measured to estimate arterial stiffness. Multivariable linear regression analyses assessed the relationship between AMH and each measure of arterial stiffness. Thirty-eight participants were recruited (29% early stage CKD, 42% advanced-stage CKD, 18% CKD treated with dialysis, 11% CKD treated with transplantation) with a median age of 44 years (IQR: 27). Age-adjusted models estimated the relationship between AMH and each measure of arterial stiffness to be statistically significant, though age was the primary driver of each relationship. Studies with larger sample sizes are needed to examine this further in addition to investigate other sex-specific cardiovascular risk factors for males living with CKD.Item Open Access Mixture Model Analysis with Misclassified Covariates: Methods and Applications(2024-09-20) Zhang, Ruixuan; Shen, Hua; Kopciuk, Karen; Liu, Juxin; Lu, XuewenMixture models are crucial for analyzing data with underlying sub-populations. Misclassification introduces discrepancies between observations and true values, which can severely bias parameter estimation, especially for mixture models when subgroups are not easily identifiable. We propose a method to enhance parameter estimation within the framework of mixture models, and mitigate the impact of misclassified covariates by utilizing them as surrogates in the Expectation-Maximization algorithm. Simulations consider both non-differential and differential misclassification with varying sample sizes, sensitivities, specificities, subgroup proportions and misclassified covariate proportions. Results demonstrate robust performance compared to naive or ad hoc approaches ignoring the misclassification issue, even under challenging conditions, such as low sensitivity and specificity for the misclassified covariate, or small sample sizes. For illustration, we apply our method to the 2015 Behavioral Risk Factor Surveillance System data. We conclude with a discussion of the implications of our findings and directions for future research.Item Open Access Synthesis of 2-arylpyridines by the Suzuki-Miyaura cross coupling of PyFluor with hetero(aryl) boronic acids/esters and Synthesis of ring oxidized phthalocyanine metal fluorides(2024-10-02) Ramanayake, Dewni Jayathma; Love, Jennifer Ann; Derksen, Darren Jason; Welch, Gregory CharlesRecently, there has been considerable interest in Sulfonyl fluorides owing to their distinctive chemical and biological characteristics. The exceptional strength of the S-F bond and the S(VI) center is responsible for the inertness and stability of sulfonyl fluorides against reactions such as hydrolysis, and reduction. However, the C-S bond of sulfonyl fluorides has been considered unreactive until recently. In particular, the activation of the C-S bond under Suzuki-Miyaura coupling conditions has not been extensively investigated. In chapter 2, we present the Suzuki-Miyaura cross-coupling reaction of pyridine-2-sulfonyl fluoride (PyFluor) with hetero (aryl) boronic acids and pinacol boronic esters. With Pd(dppf)Cl2 as the catalyst, the reaction can be carried out within a temperature range of 65 °C to 100 °C to produce 2-aryl pyridines as the product with yields spanning from moderate to good. This approach enables the synthesis of heteroatom-rich biaryls, which are important in the field of drug discovery. Phthalocyanine (Pc) ligands are chemically and thermally stable symmetric 18 π electron aromatic macrocycles, closely related to the naturally occurring porphyrins. They have been widely used as pigments/dyes, photoconducting materials, industrial catalysts, and photosensitizers in biomedical applications. The characteristics of the Pc ring, such as its solubility and electronic properties, are strongly influenced by incorporating metals inside the Pc macrocycle and by adding substituents in the alpha or beta positions of the ring. The most stable oxidation state of Pc is Pc-2, but it is redox active and can access oxidation states from Pc0 to Pc-6. The oxidation of the Pc ring can be confirmed by UV-Visible spectroscopy, Nuclear Magnetic Resonance (NMR) Spectroscopy, and single-crystal X-ray diffraction. Ring oxidized and reduced metallophthalocyanine (PcM) compounds have not been extensively investigated (and especially, not generally isolated) possibly due to the high reactivity of these complexes. In chapter 3, we detail a preliminary study on the synthesis of substituted and unsubstituted ring-oxidized phthalocyanine metal fluorides, using a range of strong oxidizing agents which also incorporate fluorides.Item Open Access Defining the role of the pore-forming apolipoprotein L APOL7C in a Leishmania infection(2024-09-24) Cedeno, Eymi; Canton, Johnathan; Yates, Robin; Surewaard, Bas; Ousman, Shalina; Finney, Constance; Peters, NathanLeishmaniasis, is a neglected tropical disease caused by infection with the intracellular parasite Leishmania. The parasite targets phagocytic cells, including dendritic cells (DCs), where it proliferates and spreads, leading to various forms of the disease, from cutaneous lesions to visceral organ damage. Despite the clinical significance, the molecular interactions between Leishmania and DCs remain largely uncharacterized. Dendritic cells, particularly conventional dendritic cells (cDCs), are pivotal in generating cytotoxic T lymphocyte (CTL) responses crucial for controlling Leishmania infections. The cross-presentation ability of cDCs has been identified as a key process in mounting these immune responses, primarily studied in murine models. However, the molecular mechanisms underlying the cross-presentation of Leishmania antigens by cDCs are still not fully elucidated. In this study, we investigated the role of apolipoprotein 7C (APOL7C), a cDC-specific pore- forming protein, in Leishmania infection. Our results show that that APOL7C, is upregulated in response to a Leishmania infection. In addition, we find that APOL7C is recruited to the parasitophorous vacuole (PV) containing Leishmania parasites, particularly in late-stage PVs and that its recruitment creates damage in the membrane of the PV. Furthermore, our data showed that APOL7C recruitment to these compartments is dependent on the NADPH oxidase and that its insertion is voltage dependent. Interestingly, this recruitment of APOL7C appears to diminish the cross-presentation of Leishmania derived antigens of our infected cell lines in our in-vitro experiments. However, in our in vivo infection model using an Apol7c-/- mice we identified differences in the immune response in mice following inoculation of the ear. Following the course of infection the absence of Apol7c -/- mice showed a decrease in ear lesion at week 7 with higher parasite burden in the dermis. These results showed the relevance of APOL7C in a Leishmania infections new insights into the molecular mechanism underlying its role .Item Open Access Obstacle Detection and Avoidance System for Unmanned Aerial Vehicles Based on Monocular Camera(2024-09-27) Yu, Mingrui; Leung, Henry; Bisheban, Mahdis; Carriere, JayUnmanned Aerial Systems (UAS), commonly known as drones, are aircraft systems without a human pilot onboard, controlled remotely or autonomously. Algorithms like YOLO (You Only Look Once) for object detection and pathfinding algorithms like A* (A-Star) can quickly navigate around large, static objects like buildings or trees. However, detecting small objects and handling dynamic aerial environments remain challenging. To address this, we introduce an innovative system for small object detection and real-time path planning using a monocular camera. Our dual-stage system combines traditional detection methods like background subtraction with advanced deep-learning techniques for improved reliability to create initial detection zones, further refined by target tracking methods for increased accuracy and depth predictor for getting estimated distance. Additionally, we have developed a new path planning algorithm, Circle Rapidly-exploring Random Trees-star (Circle RRT*), for effective obstacle avoidance. Our Obstacle Detection and Avoidance architecture navigates dynamic conditions with greater precision and speed in identifying small targets.Item Open Access Spatio-Temporal Modelling of Wind Power Ramps in Alberta(2024-09-27) Mahmoudi Gharaie, Maryam; Sezer, Deniz; Zareipour, Hamidreza; Wood, David; Aminghafari, MinaThe goal of this thesis is to model wind power ramps using a three-state Markov chain. The ramp detection technique employed is known as L1-SW in the literature. Within the Markov chain, the states’ transition probabilities are governed by a Gaussian process with a separable spatiotemporal covariance function, designed to capture the space-time dependencies across wind farms. The three states of the Markov chain are ramp up (+1), ramp down (-1), and non-ramp interval (0). The parameters of this model are estimated using a Bayesian inference framework, specifically employing no U-Turn Sampler (NUTS), which is a Hamiltonian Monte Carlo (HMC) Method. The inference procedure is implemented using RStan, an interface for working with Stan in R. The results demonstrate that our model effectively captures the properties of wind power ramps. This model is then extended to predict the ramping behavior of future, not-yet-established wind farms.Item Open Access Healthcare Utilization Among Young Adult Survivors of Childhood Cancer in Canada: The Role of Patient-Level Factors(2024-09-20) Drummond, Rachelle Marie; Schulte, Fiona; Campbell, Tavis; Reynolds, Kathleen; Ronksley, PaulBackground: Survivors of childhood cancer (SCC) face substantive risks for developing late effects (LE) from their cancer treatments due to disruptions in crucial periods of physical and social development while undergoing cancer treatment (Tonorezos et al., 2022; Baker & Syrjala, 2018). The inappropriate use of healthcare services, whether underutilization or overutilization, may jeopardize the effective risk-based prevention and management of LE among SCC. In addition, inappropriate healthcare utilization (HCU) may contribute to unsustainability and inefficiency in the healthcare system, creating challenges for supporting the growing population of survivors in Canada. Despite existing knowledge that young adult (YA) SCC are at a heightened high risk for the development of LE and life-long complications from their treatments, limited research exists that describes HCU among this population. The two aims of this study were to 1) identify and explore the associations of survivor’s demographics (i.e., sex, gender, age, race, geographic location, SES), knowledge of cancer history and risks, and psychological factors (i.e., anxiety, depression) and perceived vulnerability with healthcare utilization; and 2) examine the relationships among demographic, clinical, and psychological patient-level factors with HCU among YA SCC. Methods: Canadian YA SCC (n=123; 31% male; mean age=28.19yrs, mean time post treatment= 16.56yrs) diagnosed <18 years of age; and >5 years from diagnosis and/or >2 years from treatment completed the Self-Report Survey of Cancer Knowledge (Kunin-Batson et al., 2016), and the Self-Report Survey of Core Health Beliefs (Tercyak et al., 2004), to assess knowledge of cancer history and risks and perceived vulnerability, respectively. Survivors completed the Patient-Reported Outcomes Measurement Information System (PROMIS) SF v1.0 Anxiety 8a and the PROMIS SF v1.0 Depression 8a to assess levels of anxiety and depression respectively. To assess HCU, survivors reported the number of times that they saw a doctor within the last 2 years, in relation to their cancer diagnosis. A bivariate logistic regression model examined associations between YA SCC’s demographics, knowledge of cancer history, and psychological factors with HCU. Results: Survivors reported a wide range of HCU rates over the past 2 years (median= 3-4 visits). The number of reported visits ranged from 0-20+ visits. Despite 45.5% of reported health problems being attributed to mental health, psychiatrists and psychologists/counselors were the third and fourth least utilized types of providers, respectively. A logistic regression model was conducted to assess the associations between HCU and patient-related factors. The model was significant X2(8) =23.68, p=0.003, and accounted for 29.3% of variance in healthcare utilization among YA SCC (NagelKerke R2= 0.293). Anxiety was the only independent variable that contributed significantly to the model (p<0.001), and higher anxiety scores were associated with increased odds of HCU. Conclusion: Anxiety levels were a significant predictor of HCU rates within this population, whereby higher anxiety scores were associated with higher HCU rates. Based on the findings of this study, behavioral interventions could be beneficial in reducing anxiety among YA SCC and promoting appropriate risk based HCU that support the long-term well-being of survivors, and the sustainability of the healthcare system.Item Open Access Development of Economically Profitable and Environmentally Benign Alternatives for Low-cost Carbon Resources Valorization(2024-09-16) Omidkar, Ali; Song, Hua; Kibria, Md; Hu, JinguangA global phenomenon of depletion is observed in high-quality light crude oil reserves, leading to a concomitant rise in their cost. Consequently, the future of petroleum utilization is anticipated to shift towards heavy oil resources, encompassing heavy, extra-heavy crude oils, and residues generated during the refining process. It is the motivation for the first research work about Techno-economic and life cycle assessment of bitumen upgrading using methane. As a result of the techno-economic analysis, the MAU process has the highest IRR and the shortest payback period for all scenarios. A comparison was also made between the proposed MAU process and other research studies. Results indicate that MAU with the total operating cost of (34.1 $/bbl. bitumen) and transportation cost of (1.1 $/bbl. Bitumen for 500 km pipeline transportation) has the best results. Based on the LCA results, using methane instead of hydrogen can decreases the CO2-eq/kg of fuel by 11%. However it can be proved that the methane upgrading of bitumen is highly feasible, the main problem remains. Bitumen is still a fossil-based fuel with high emissions. So in another research TEA and LCA of the waste cooking oil upgrading was carried out to assess the potential of methane upgrading for bio-based fuels. The production costs for the methane-assisted catalytic process are 0.365 $/kg renewable diesel and for hydrotreating and alkali-catalyzed process, the production costs are 0.574 $/kg renewable diesel and 0.513 $/kg biodiesel, respectively. The economic results have also been compared with other research and it was found the total production cost of the new process is minimal, however total capital investment is a bit high. The CO2-eq/MJ fuel is also decreased by 23% compared to commercial hydrotreating. The application of methane for upgrading fossil-based and bio-based fuels was proved, however, the pyrolysis of organic solid waste can be another application of methane as a hydrogen donor. In another research upgrading of waste cooking oil with natural gas was assessed. According to the economic evaluation, using natural gas significantly reduces the minimum selling price (MSP) of renewable diesel. In this study, $3.5/gal is the minimum selling price, which is 22% lower compared to similar plants in other literature reviews. A Monte Carlo simulation was also performed to investigate the uncertainty, and the results indicated that, with a probability of 50%, the net present value (NPV) is greater than the NPV calculated deterministically. Based on the results of the life cycle assessment, the newly proposed process emits 66% less amount of greenhouse gases than other commercial processes. The second part of this thesis delves into the experimental realm, introducing a novel non-thermal plasma-assisted catalytic process operating at ambient pressure and temperature for bio-oil upgrading with methane as the hydrogen donor. In this section based on the specific characteristics of rhodium and gallium nitride, Rh as active metal and GaN as support were selected. Based on the TEM-EDX results the size of nanoclusters mostly is on the interval of 1nm to 1.5 nm. The total acid number of feed decreased by 60% showing the synergic effect of catalyst and non-thermal plasma. The PONA analysis showed that saturation of olefins conversion to iso-paraffins has happened inside the plasma medium.Item Open Access Improving Classification and Segmentation of Choroidal Lesions by Addressing Data Limitations with Patch-Based Approaches(2024-09-19) Biglarbeiki, Mehregan; Far, Behrouz; Crump, Trafford; Messier, Geoffrey; Bento, MarianaChoroidal nevi are benign ocular lesions that can progress to malignant forms like choroidal melanoma. Recent advancements in Deep Learning (DL) have shown potential in detecting ocular diseases, automating eye reviews, and facilitating timely treatment. However, these models require extensive labelled data, which is challenging to acquire due to the associated labeling costs. This limitation affects the optimal performance of DL models, leading to underexplored applications in this domain, with only a few studies available. This thesis presents three studies aimed at overcoming data limitations and enhancing model performance for the classification and segmentation of melanocytic choroidal tumors in fundus images. The first study involved binary classification of choroidal nevi and healthy subjects, using fundus images from the Alberta Ocular Brachytherapy dataset. Pre-trained models—ResNet50, DenseNet121, EfficientNetB7, and YOLOv8n—were evaluated. Results indicated that training on image patches rather than full-size images, combined with data augmentation to address noisy images and low-contrast lesions, resulted in the YOLOv8n model achieving the highest accuracy of 92.61%. The second study aimed to segment choroidal nevi lesions from fundus images. U-Net and YOLOv8n segmentation models were trained on the Alberta Ocular Brachytherapy dataset and validated on the Wills Eye Hospital dataset. The YOLOv8n model achieved Dice Coefficient scores of 0.833 and 0.764 for the Alberta and Wills datasets, respectively, when trained on both full-size images and image patches, along with the proposed post-processing methods. In the final study, a YOLOv8n model classified choroidal melanoma and nevi lesions from montage fundus images. The model’s performance was evaluated under two pre-training scenarios. The model pre-trained on ImageNet and fine-tuned on our dataset achieved an accuracy of 92.25%, outperforming the model pre-trained on ImageNet and fine-tuned on the Kaggle EyePACs dataset before the final fine-tuning on our dataset. Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to enhance model interpretability, providing ocular oncologists with insights into the model’s predictions. Overall, these studies emphasize the significance of DL models in automating the detection of melanocytic choroidal lesions and improving their classification and segmentation performance.Item Open Access Factorization Systems for Discrete Homotopy Theory(2024-09-23) Hardeman Morrill, Rachel; Bauer, Kristine; Laflamme, Claude; Cockett, Robin; Cunningham, Clifton; Scull, LauraHomotopy theory is a well-studied field of mathematics which allows us to determine which spaces can be obtained by a deformation of another. Analogous theories have been developed for the mathematical objects called graphs. In this thesis, I further develop one of these homotopy theories for graphs, called A-homotopy theory, by constructing a covering graph theory, completing the work of my Master’s thesis. Covering graphs allow us to factor graph homomorphisms through other graphs using lifts. Factoring morphisms is an important part of finding structure on a category, and that structure is necessary for us to have a fully developed homotopy theory on the category. An example of such a structure is Hurewicz model structure on the category of spaces, which involves covering spaces. We show that there is no analogous Hurewicz model structure on the category of graphs. Instead, we define a new homotopy equivalence for graphs and a cloven weak factorization system structure on the category of graphs using path objects. This structure allows us to factor any morphism by a strong deformation retract followed by a morphism with the homotopy lifting property. This is a particularly useful factorization, which leads to a complete re-framing of A-homotopy theory.Item Open Access Entangled Methodologies for Participatory Multispecies Futures(2024-09-20) Bista, Priyanka; Taron, Joshua; Semple, William; Eiserman, Jennifer; Stamm, Marcelo; King, Andrew; Stewart, SallyThe Anthropocene is most known for its impact on biodiversity loss; however, it’s also an era that negatively impacts and excludes the most marginalized communities. This disconnect is particularly evident and further exacerbated in contexts like Koshi Tappu, Nepal, fraught with increasing daily human-wildlife conflict as a result of being home to over 80,000 people while situated directly adjacent to the Koshi Tappu Wildlife Reserve (KTWR). Also located in a sensitive geopolitical region next to the border of India, macroeconomics, political tumult, and ethnic conflicts further heighten these pressures and conflicts. My attempt through the DDes was to understand how the field of design, particularly multispecies design, could contribute to this contentious, conflicted context. The research objectives aimed to develop a multispecies design methodology that helps build understanding, foster empathetic relationships, and mitigate conflict between human and nonhuman stakeholders, particularly focused on conflict species and local communities living with them. Additionally, I aimed to contribute new case studies from the Global South and explore potential practice platforms through teaching and practice that could directly support and advance this work. The research revealed four key insights: firstly, that the methodology is a two phased process, that gives space to immerse in understanding, unpacking, and documenting the conflict space before moving to the solution space. Secondly, if we are to engage people, participatory design methods need to go hand-in-hand with multispecies design methods. Thirdly, to engage communities, each step of the process needs to include “learning” opportunities that unlock inherent learning potential in communities and landscapes. Fourthly, the methodology artifact is a library of tools designed to support facilitators, whether designers or educators, in engaging participants, whether students or communities, through a participatory multispecies design process. Finally, I feel that I’ve only scratched the surface of the enormous potential inherent in developing a Participatory Multispecies Learning Tool Library that operates as a support structure for engaging in Multispecies Conflicts worldwide.Item Open Access An Exploration of the Issue of Value in a Landscape Architectural Practice(2024-09-19) Koudys, Ron; Fox, Kristoffer; Dall'ara, Enrica; Scarfo, Robert; Hlimi, Tawab; Nash, DiarmuidThis doctoral thesis employs a Design Science Research (DSR) approach to investigate and demonstrate the values within landscape architecture in the context of my own professional practice. This study integrates empirical research, self-reflective case studies, and theoretical frameworks to create actionable knowledge for the field. The study endeavours to answer two questions. What value has my practice provided in the areas of Economics, Environment, Society and Aesthetics. Secondly, what personal values have defined the provision of these benefits and how have they changed over the course of my career.Item Open Access Hydrogen dissociative adsorption on pipeline steels in high-pressure gaseous environments(2024-09-16) Sun, Yinghao; Cheng, Frank; Egberts, Philip; Hugo, RonaldHydrogen is acknowledged as a key player in energy transition and the pursuit of achieving the net-zero target. Pipeline can serve as an ideal transportation method for H2 due to its high efficiency, large capacity, and relatively low cost. However, H2 pipelines are facing the problem of Hydrogen Embrittlement (HE), which might cause catastrophic failure. However, due to the size limitation, only atomic H can enter the pipeline steel and lead into HE. Thus, research on atomic H generation on steel surface, i.e., dissociative adsorption, is essential to H2 pipelines application. Up to date, there have been limited investigations on hydrogen dissociative adsorption at irregularities on pipeline steel. In this work, hydrogen dissociative adsorption on steel crystalline plane is studied to verify the feasibility of simulation methodology. Models of typical irregularities on pipeline steel surface, i.e., grain boundary, dislocation, non-metallic inclusion are constructed. To the authors’ best knowledge, it is the first time to develop microstructure models considering surface effect. It is found that interior high angle grain boundary, edge dislocation core and the sites under tensile strain, Fe side of Al2O3 interface, are preferential sites for hydrogen adsorption. The bonding mechanism for hydrogen adsorption is determined to be orbital hybridization. Electrons will shift to adsorbed H atoms from nearby Fe atoms and Al/O atoms. Partition function is applied to indicate that high pressure and low temperature are favorable for hydrogen dissociative adsorption. Oxygen included gas impurities can inhibit hydrogen adsorption by competitive attraction of electrons, while CH4 can also slightly inhibit hydrogen dissociative adsorption. Based on literature review and conducted investigations, perspectives on atomic H generation and HE under gaseous environment, and inhibiting effect of certain impurity gases on hydrogen dissociative adsorption are provided.Item Open Access The Changing Sense of Who I Am and What I Need: Female Athletes’ Evolving Perspectives on Re-negotiating Identity and Social Support after Sports-Related Concussions(2024-09-17) Kintzel, Franziska; Domene, José F.; Mudry, Tanya; Bridel, WilliamSports-related concussions and their impact on athletes are slowly becoming a greater focus of research, leading to greater awareness within and outside of sports. Associated symptoms are manifold, including their invisibility to outsiders. Female athletes are at higher risk of experiencing sports-related concussions and generally report experiencing more severe and prolonged symptomology compared to male athletes. Despite extensive research on the physiological and psychosocial impact of sports-related injuries, little is known about female athletes’ psychological experiences post-concussion, particularly concerning possible changes in their identity and appropriate social support postconcussion. Within this dissertation, which was conducted using interpretative phenomenological analysis, I examined how female athletes made sense of their lived experiences following sports-related concussions concerning their sense of identity, how they navigated possible changes, and what types of support they received and found helpful regarding their recovery. Manuscript 1 presents an overview of relevant research regarding the research questions, while Manuscripts 2 and 3 present different aspects of the study findings. Manuscript 2 focuses on participants’ sense-making of identity postconcussion. The themes that were constructed highlight the polarizing experience of engaging with one’s athletic identity, making sense of internal versus external perceptions of identity change and crisis, and navigating grief, loss, and other emotions. Manuscript 3, which presents themes related to social support post-concussion, reflects the role of agency and ownership over one’s own healing, exploring the pitfalls of support, unveiling the beneficial facets of support, and the importance of a need for change. These findings are integrated through a proposed concussion management model that focuses on compassion, agency, resilience, and education (i.e., CARE-W) while also suggesting future directions for further research.Item Open Access LGBTQ+ Patients’ Experiences of Harm in Psychotherapy: A Scoping Review & Reflexive Thematic Analysis of the Peer-Reviewed Literature(2024-09-19) Furlani, Noah Bauschen; Mudry, Tanya; Maroney, Meredith; Russell-Mayhew, Shelly; Mudry, TanyaHarmful experiences in therapy, such as microaggressions and sexual boundary violations, occur more frequently than is commonly thought. Existing research shows that while LGBTQ+ people seek out psychotherapy in greater proportion than their heterosexual and cisgender counterparts, they also tend to report more harmful experiences in therapy. Harmful experiences in therapy negatively affect therapy outcomes and may worsen patients’ psychological well-being. Therapists also have a long history of harm against sexual and gender minority patients. In order to improve the safety and efficacy of psychotherapy for LGBTQ+ patients, a better understanding of their harmful experiences in therapy is needed. In this thesis, I first conducted a scoping review to identify the relevant peer-reviewed literature on LGBTQ+ patients’ experiences of harm in therapy. Our review identified 61 articles based on the inclusion criteria. Articles’ participant demographic data, focus population, and publishing information was charted. To identify forms of harm, I further conducted a Reflexive Thematic Analysis on the articles extracted during the scoping review. Through this process, I generated three superordinate themes: (1) conversion therapy-related harms; (2) discrimination and prejudice in psychotherapy; and (3) heterosexist and cissexist enactments and misattunements. These results are discussed in light of current events and the related peer-reviewed literature, noting increases in conversion therapy targeting trans and nonbinary people and anti-trans legislation. In addition, I also highlighted several gaps in the extracted literature, including insufficient attention to major ethical breaches, such as violations of confidentiality and sexual boundary violations. Finally, I note implications of these results for clinical practice and training.Item Open Access Reconstruction of early Eocene paleoclimate and paleo-environment in Guchengzi Formation, Fushun Basin, NE China, using biomarkers and aromatic compounds(2024-09-20) Xu, Xianghe; Huang, Haiping; Larter, Steve; Chen, Zhangxing (John); Snowdon, LloydOne hundred and twenty-four coal and coaly shale samples were collected from a 13-meter-thick coal open mining section of the early Eocene Guchengzi Formation in the Fushun Basin, NE China. The coals and coaly shales from the Eocene Guchengzi Formation were deposited in an oxic environment and are classified within the subbituminous A rank. Rock-Eval hydrogen index values indicate the presence of Type II2-III kerogens. Molecular compositions were determined using gas chromatography-mass spectrometry (GC-MS) to diagnose source inputs and assess depositional conditions. The n-alkane distribution in these samples is characterized by a dominance of long-chain odd-numbered n-alkanes, exhibiting high odd-to-even preference. The isoprenoid distribution is marked by a high pristane/phytane (Pr/Ph) ratio, which is indicative of oxic conditions during organic matter formation. The samples show high concentrations of bicyclic sesquiterpanes, tricyclic diterpanes, tetracyclic diterpanes, and hopane homologs, along with low concentrations of steranes and the absence of oleanane. This suggests a dominance of gymnosperm biomass input with significant bacterial activity. Aromatic hydrocarbons in the samples are dominated by naphthalene, phenanthrene, and their alkylated homologs, with a low abundance of four- and five-ring aromatic hydrocarbons. Various higher plant-derived aromatic hydrocarbons were identified, including 1,2,5-trimethylnaphthalene, 1,2,5,6-tetramethylnaphthalene, cadalene, 6-isopropyl-1-isohexyl-2-methylnaphthalene, 1,7-dimethylphenanthrene, simonellite, and retene. The distribution of combustion-derived polycyclic aromatic hydrocarbons such as fluoranthene, pyrene, benzo[a]anthracene, and various benzofluoranthenes and benzopyrenes suggests that forest fires occurred in the study area during the early Eocene period. Molecular constituents provide valuable insights into the paleoenvironmental conditions and the type of vegetation contributing to the organic matter in the Fushun Basin during the early Eocene. The geochemical data highlight the complex interplay between terrestrial and aquatic inputs, bacterial activity, and environmental factors such as forest fires, all of which played a significant role in shaping the depositional environment of the Guchengzi Formation coals and coaly shales.Item Open Access Deconvolution of spatiotemporal transcriptomic heterogeneity in the glioblastoma ecosystem(2024-09-23) Thoppey Manoharan, Varsha; Morrissy, Sorana; Gallo, Marco; Mahoney, Douglas; Neri, PaolaGlioblastoma (GBM) is the most common and lethal primary brain malignancy in adults, characterized by therapeutic resistance and inevitable relapse. Major clinical challenges are imposed by extensive intra-tumoral heterogeneity, diffuse infiltrative growth of the tumor, and bi-directional interactions with diverse non-malignant cell-types within the brain tumor microenvironment (TME). A better understanding of how the tumor cells organize spatially and interact with the TME to promote growth and invasion may reveal opportunities for improved therapeutic strategies. In this thesis, I explore transcriptional heterogeneity within the glioblastoma ecosystem using spatially profiled, temporal samples of GBM xenograft models. The species-specific distinction of the human tumor and mouse TME, coupled with spatial resolution, overcomes previous limitations in studying the invasive front and delineating co-existing non-malignant components within the tumor. By applying a novel computational framework based on unsupervised deconvolution, I characterize a compendium of 15 tumor cell gene expression programs set within the context of 90 mouse brain and TME cell types, cell activities, and anatomic structures. This approach reveals the spatial organization of tumor programs along an axis corresponding to tumor density and distinct colocalization patterns with spatiotemporally varying TME components. Notably, tumor-associated macrophages and reactive astrocytes colocalized with the tumor early in its growth, while an outward gradient of invasion programs, centered on hypoxia, was observed with tumor progression. Moreover, distinct tumor programs aligned with well-documented routes of GBM invasion including the white-matter tracts, perivasculature and parenchymal routes. Ligand-receptor analyses highlighted neuronal and extra-cellular matrix (ECM) signaling along these routes, and further analyses indicated that these routes could be distinguished by the expression of tumor and TME-derived ECM molecules. Lastly, using a network-graph of predicted protein-protein interactions, I identified sub-modules of genes serving as program network hubs that were highly prognostic in patient datasets. Taken together, spatial profiling of xenografts has revealed a granular repertoire of transcriptional programs and provides a basis for rational targeting of tumor and/or TME niches within the GBM ecosystem, paving the way for improved therapeutic interventions.Item Open Access Internet-Delivered Cognitive Behavioral Treatment for Chronic Pain in Adolescent Survivors of Childhood Cancer: A Single-group Feasibility Trial(2024-09-20) Patton, Michaela; Schulte, Fiona; Birnie, Kathryn; Carlson, Linda; Truong, Tony; McMurtry, MeghanIntroduction: Two-thirds of survivors of childhood cancer experience long-term side effects from treatments, like chronic pain. No pain management interventions have been tested on youth survivors of childhood cancer. Including parents in treatment and understanding parents’ own experience with pain can help improve youth outcomes. Web-based Management of Adolescent Pain (WebMAP) is an evidence-based, online intervention that includes parents, but has not yet been tested on survivors of childhood cancer. Methods: Survivors and parents were given online questionnaires about their pain. The feasibility and acceptability of WebMAP in survivors of childhood cancer and their parents was evaluated. Qualitative interviews were conducted and analyzed using inductive thematic analysis. Results: The prospective observational study found that half of survivors of childhood cancer with chronic pain have parents with chronic pain. The intervention study found that WebMAP met acceptability benchmarks but did not meet all feasibility benchmarks. Themes that emerged from qualitative interviews included “We found the program useful” and “There were areas of the program that could be improved upon”. Conclusion: Pain is prevalent in both survivors of childhood cancer and their parents. WebMAP is acceptable but not feasible in this specific subset of survivors of childhood cancer. WebMAP may be better suited for survivors whose primary concern is pain. Survivors of childhood cancer may benefit from an intervention that addresses multiple common health sequela in this population. Qualitative interviews provide helpful considerations for pediatric health interventions, more broadly.Item Open Access Deep learning methods for classifying disease subtypes in multiple sclerosis based on clinical imaging and non-imaging data(2024-09-23) Soleymani, Mahshid; Zhang, Yunyan; Bento, Mariana Pinheiro; Forkert, Nils Daniel; MacDonald, Matthew EthanMultiple sclerosis (MS) is a common inflammatory demyelinating and neurodegenerating disease of the central nervous system impacting over 2.8 million people worldwide. Most people start MS with a relapsing-remitting form (RRMS), yet no two persons have the same disease course. Many of them will develop a secondary-progressive course (SPMS) despite treatment, causing dramatic health and socioeconomic consequences. Early accurate measurement of disease activity will permit early effective treatment for improved prognosis. But there is no established method to classify these two subtypes beforehand clinically. By leveraging the power of deep learning such as convolutional neural networks (CNNs), this project aims to optimize personalized disease characterization using standard clinical data especially brain magnetic resonance imaging (MRI). Specifically, based on 140 clinical participants with RRMS or SPMS, the research targets phenotype prediction through a series of development and validation processes. These included data optimization, model development and testing based on both 2D- and 3D- CNN models, and model interpretation using a recognized method called gradient-class activation mapping (Grad- CAM). Results showed that axial images normalized with a Z-score like approach were most feasible. Both the 2D and 3D models achieved >80% accuracy in predicting RRMS and SPMS, where combining both MRI and clinical variables appeared to perform better than either data type alone. The Grad-CAM analysis helped discern critical brain areas related to each MS subtype. These findings underscore the potential of deep learning based completely on clinical care data to detect disease activity, marking early diagnosis and personalized treatment possible.