Arts and Science, Faculty of

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Now showing 1 - 5 of 1362
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    Neural correlates of narrative structure during naturalistic audiovisual film using functional magnetic resonance imaging
    (Lethbridge, Alta. : University of Lethbridge, Dept. of Neuroscience, 2023) Haines, Christina; Ekstrand, Chelsea; Gibb, Robbin
    A narrative is defined as a description of interconnected events, whereby forming narratives requires sustained attention and simultaneous integration of information to navigate and track events and assign them along an immersive timeline (Martinez-Conde et al., 2019). Narratives, in the form of film, plays, and television, offer a unique opportunity to assess brain functions in situations more akin to the “real-world”. However, most neuroimaging studies examining narrative formation have used static stimuli (e.g., still images, disconnected sentences, or incoherent narratives) that do not encapsulate the complexity of narrative formation in the everyday life. It is currently unknown how the brain processes “real-world” information into coherent narrative events. The current research uses data from the Naturalistic Neuroimaging Database (Aliko et al., 2020) to examine the neural correlates of narrative processing using functional magnetic resonance imaging (fMRI). In four experiments, we assessed neural synchrony patterns implicated in long-term narrative processing and identified networks associated with distinct phases of narrative processing and conveyed the dynamic changes of cognitive demands as a narrative evolves. Results from this study emphasize the evolving cognitive demands intrinsic to narrative structure, reflecting dynamic changes in neural synchrony. These findings extend beyond research advancement, by bridging the gap between cognitive neuroscience and “real-world” narrative processing.
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    Molecular standards for analytical ultracentrifugation: investigating the suitability of double-stranded DNA
    (Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry, 2023) Ranasinghe, Maduni Charuni; University of Lethbridge. Faculty of Arts and Science; Demeler, Borries
    This thesis focuses on the development of molecular standards to validate analytical ultracentrifugation (AUC) instruments, alongside an exploration of multiple applications of AUC. The goal of the main study is to address the critical need to develop a robust molecular standard for validating AUC instruments, with a specific emphasis on evaluating double-stranded DNA molecules as a potential candidate. By extensive investigation into the hydrodynamic properties of different topologies of double-stranded DNA at a wide range of temperatures, this study reveals the potential of linear and nicked double-stranded DNA as a reliable standard for AUC, contributing to the accurate characterization of macromolecules in solution. Supplementary research findings, as detailed in the attached publications presented in the attached appendix, further illustrate the versatility of AUC in various scientific domains. In one study, we employed AUC as a powerful technique to measure the sedimentation and diffusion coefficients of DNA minicircles to validate the elastic theory results obtained from our other collaborator. Also, it explores the impact of DNA supercoiling-induced shapes on minicircle hydrodynamics. In another collaborative effort, we study the oligomerization behavior of a de novo designed metalloprotein for photocatalytic hydrogen evolution, leveraging AUC for comprehensive characterization. These collective studies highlight the indispensable role of AUC in the characterization of macromolecules in solution, with applications ranging from DNA dynamics to functional protein characterization, and they demonstrate the crucial importance of reliable molecular standards in enhancing the accuracy of AUC measurements. Together, they contribute to the advancement of analytical science and its applications across diverse research domains.
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    Measuring developer experience with abstract syntax trees
    (Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, 2023) Deutekom, Steven M.; University of Lethbridge. Faculty of Arts and Science; Rice, Jacqueline E.; Anvik, John
    Accurately representing a developer's programming knowledge and experience is difficult. Traditional metrics rely on counting the number of times a developer has used or made changes to pieces of code. When a developer has modified a file in the past they are less likely to introduce defects with a change. However, these metrics do not contain any general information on the structure or purpose of a piece of code and are only useful when developers work on a piece of code more than once. We investigated the use of several new metrics based on abstract syntax trees (ASTs) as a possible way to more completely measure a developer's experience. By using the ASTs of code previously modified by a developer we may be able to identify their experience with a piece of code they are modifying even if they have never modified that specific code before. Through statistical analysis and machine learning predictions we show that AST-based metrics capture a more general programming experience than count-based metrics. In their current form, AST-based metrics do not offer any significant improvements over existing metrics for defect prediction. However, our work offers a starting point for future use of ASTs for representation of knowledge and experience in defect prediction and other relevant areas.
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    A computational model of Blackfoot noun and verb morphology
    (Lethbridge, Alta. : University of Lethbridge, Dept. of Indigenous Studies, 2023) Kadlec, Dominik Miroslav; University of Lethbridge. Faculty of Arts and Science; Genee, Inge; Arppe, Antti
    This thesis describes the construction of a computational model of Blackfoot word structure. This model was developed so that it could provide a foundation for Blackfoot language technologies such as spelling and grammar checkers, search suggestion generators, paradigm generators for pedagogical purposes, intelligent dictionaries, automated corpus parsers for linguistic research and more. Many Indigenous languages in Canada have been declining in use. In response, many Indigenous communities and activists have implemented revitalization strategies which vary in effectiveness. One way to help language efforts to be more effective is to ensure that tools for research and revitalization are freely available to community members. In the 21st century this can be achieved in part through technology, particularly with the help of the internet, which offers information freely (in most cases) to those who wish to access it. In this thesis I describe the early developments of a project that will be used to augment currently available digital resources and provide a basis for future technology for the Blackfoot language. I use Finite State Transducer technology to develop a computational model of Blackfoot noun and verb morphology and test the model using a corpus of modern Blackfoot text that was constructed from a curated collection of available texts.
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    Improving gene therapy analysis with multi-wavelength analytical ultracentrifugaton methods
    (Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry, 2023) Henrickson, Amy; University of Lethbridge. Faculty of Arts and Science; Demeler, Borries
    Over the past few years, research into gene therapies has dramatically increased, with thousands of drug candidates in clinical trials. However, only a few are available on the market today, highlighting the need for improved analysis methods that can help validate the drug development process. The challenges associated with gene therapy analysis vary with different vector types and compositions. The main challenges for lipid nanoparticles (LNPs), a non-viral vector, are their large size and inherent heterogeneity. The challenge for adeno-associated viruses (AAVs), a viral vector, is differentiating between the full AAV capsid and the product-related impurities due to their similar hydrodynamic radii and surface properties. For both vectors, these challenges prevent their accurate quantification and characterization by many chromatography and size-based techniques. We have employed analytical ultracentrifugation (AUC) to improve gene therapy analysis by characterizing solutes in a sample based on their molar mass, shape, and density. AUC provides high statistical certainty through bulk observations, resulting in the correct assessment of sample purity and loading states. To further improve the resolution of AUC results, we have incorporated multi-wavelength capabilities into our AUC methods, adding an orthogonal optical characterization dimension. This thesis presents considerations for the design, execution, and analysis of multi-wavelength (MW) AUC experiments, looking at cases where optical deconvolution is not possible and cases where it is. It also includes a section on using MW sedimentation velocity experiments to characterize protein-DNA interactions, providing an example of how stoichiometry can be determined from MW-AUC experiments. Further, we apply MW capabilities to several AUC methods to improve the quantification and characterization of AAVs and LNPs. This results in the precise quantification and characterization of vectors, product-related impurities, and other contaminants.