- ItemNiitsitapii heritage education: a poomiikapii approach(Lethbridge, Alta. : University of Lethbridge, Dept. of Anthropology, 2023) Weasel Moccasin, Camina N.; University of Lethbridge. Faculty of Arts and Science; Cuellar, Andrea M.This is a critical study of the current heritage management practices in southern Alberta, especially as they relate to Niitsitapii (Blackfoot) heritage sites. Two sites in particular, Head-Smashed-In Buffalo Jump and Writing-on-Stone / Aisinai’pi, are used as case studies for this research. Both of these sites have provincial, federal, and global designations resulting in layers of colonial policy focussed on how to best manage the heritage sites. Current heritage management directives and policies are discussed and dissected in order to understand the cultural values they represent and protect. These are compared and contrasted to Niitsitapii cultural values at the core of Niitsitapiiysinni (our way of life). Opinions from the Niitsitapii communities of Kainai and Piikanii were gathered and analyzed. From the responses / engagement received, themes began to emerge highlighting what is of importance, and value, for Niitsitapii people when it comes to managing Niitsitapii heritage. The document ends with discussing and presenting best practices that would benefit and support Indigenous led heritage management policy making.
- ItemUnsupervised detection of cell ensembles in rats' primary motor cortex during online and offline processing(Lethbridge, Alta. : University of Lethbridge, Dept. of Neuroscience, 2023) Nazari Robati, Peyman; University of Lethbridge. Faculty of Arts and Science; Tatsuno, MasamiMotor actions engage intricate neural processes, spanning active learning phases and crucial offline periods, notably during sleep. Online learning involves diverse neural dynamics, while sleep is known for its role in skill consolidation. While numerous studies have contributed to our understanding of information processing during online and offline learning periods, these investigations have often focused on specific learning phases, leaving the intricate relationships between diverse online learning neural activities and sleep processing relatively unexplored. Here, we embarked on a comprehensive analysis aimed at unraveling the interplay between primary motor cortex (M1) neural activity during reach-to-grasp skill learning and sleep, employing an unsupervised framework. During online training, our findings uncovered four neural dynamics related to the motor execution, with compelling evidence of their replay during post-training sleep, both in Rapid Eye Movement and Slow-Wave Sleep (SWS). Moreover, our data revealed that all cell ensembles, irrespective of their dynamics during the task, exhibited substantial reactivation during spindles coupled with slow-oscillations in SWS. Further exploration on the cortico-hippocampal communication led us to investigate the activation patterns of M1 cell ensembles during hippocampal sharp-wave ripples. Our results demonstrated the dynamic suppression and enhancement modulation of M1 cell ensembles during SWS-ripples across learning days suggesting complex cortico-hippocampal dialogues associated with sensorimotor learning task. We thus contributed to understand the extensive details of neural mechanisms underlying motor learning tasks during online and offline processing periods.
- ItemOrigins of thermalization in quantum cosmology(Lethbridge, Alta. : University of Lethbridge, Dept. of Physics and Astronomy, 2023) Osei, Michael Adjei; University of Lethbridge. Faculty of Arts and Science; Dasgupta, ArundhatiWe aim to provide the effect of accelerated frames in cosmology and identify the origins of thermalization in the evolution of the universe. We begin our discussion by discussing general relativity and cosmology, as well as their successes and failures, which leads to the need for quantum cosmology. We then discuss the canonical formulation of general relativity, which is the basis of quantum cosmology, and its issues. We constructed a wavefunction for the universe whose dynamics are governed by the Wheeler-Dewitt equation. Semiclassical approximations simplify assumptions and approximations that bring the equation closer to a form that can be more easily analyzed. The WKB method is used to approximate the wave function. We constructed a transformation that is similar to the Rindler transformation motivated by the Klein-Gordon equation in Minkowski spacetime. We performed the Bogoliubov transformation and obtained a result which suggested thermalization. However, we were not using creation and annihilation operators. To interpret this result, we calculated the density matrix and the square of the density matrix to see if the WKB state is a pure or mixed state. The result from the density matrix calculation suggested that the WKB state is a mixed state, which suggested that the result we obtained from the Bogoliubov transformation can be interpreted as thermalization.
- ItemSynthetically generated cow (Bos taurus) provides data for gait analysis in feedlot(Lethbridge, Alta. : University of Lethbridge, Dept. of Neuroscience, 2023) Goldani, Ali; University of Lethbridge. Faculty of Arts and Science; Whishaw, Ian Q.; Mohajerani, Majid H.Analysis of bovine movement and behavior is crucial in detecting their motor disorders and maintaining their welfare. Quantitative gait analysis methods have been designed to facilitate this task, but the on-site subjective assessment of the gait pattern remains prominent and depends on human expertise. Gait pattern could be assessed in feedlot cattle using AI as a substitute for the absence of human diagnosis, but creating an AI diagnosis procedure requires substantial behavioral information for training the AI tool. One solution for obtaining behavioral information is to use AI-assisted tools for diagnosis based on recordings of cattle movement. In this study, we created a three-dimensional digital representation of walking cattle to generate the required information and compare its applicability to that of the actual gait patterns. We used video recordings of cattle walking and trotting, and then used them as reference to create three-dimensional pose representations. Then, we introduced variations to these representations by altering specific aspects of the original walking cow model and its environment. We then tested the combined representations against the real data to see if they can prove useful in training a deep neural network for detecting gait pattern and features. This method can compensate for the scarcity of behavioral data, provide information to create mathematical representations of specific behaviors and be used for the development of smart-phone-based diagnosis systems.
- ItemMacroeconomic policies and external debt in Ghana: lessons from the Latin American countries(Lethbridge, Alta. : University of Lethbridge, Dept. of Economics, 2023) Narnor, Abigail Dede; University of Lethbridge. Faculty of Arts and Science; Darku, Alexander B.Managing external debt in Ghana remains challenging. This thesis examines the relationship between various macroeconomic variables and external debt in Ghana from 1970 to 2020 using the autoregressive distributed lag (ARDL) model. It also takes lessons from the Latin America (Mexico, Argentina, and Brazil) debt crisis and forecasts Ghana's external debt for the next decade (2021-2030) using the autoregressive integrated moving average (ARIMA) and ARIMA with exogenous variables (ARIMAX) models. The thesis finds that budget balance and current account balance are the only macroeconomic variables that have an impact on external debt in Ghana in both the short and long run. Interest rate on domestic debt impacts external debt in the long run, while inflation, real GDP, interest rate on external debt and money growth impact external debt in the short run. The forecasting exercise reveals that external debt will increase by 109.35% and 18.26% by the next decade based on the ARIMA and ARIMAX models, respectively.