Doctoral Theses and Dissertations

Permanent URI for this collectionhttps://hdl.handle.net/10294/2900

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Open Access
Settler school psychologists readiness to decolonize practice
(Faculty of Graduate Studies and Research, University of Regina, 2024-07) White, Michael Cornelius; Osmond-Johnson, Pamela; Spooner, Marc; McGinnis, Angela; Sorensen, Michele; Ansloos, Jeffrey
This study presents a modified grounded theory analysis of settler school psychologists’ engagement with the idea of “decolonizing” their professional practice in working with Indigenous students and their families. Data was gathered through two rounds of interviews with seven settler school psychologists across Western and Northern Canada who are active in the profession. A personalized “self-location” situates the researcher as a settler school psychologist as a means of challenging psychology’s perception of itself as an “objective” science. Decolonization theory is explored from a variety of perspectives beginning with the work of Frantz Fanon (1961/2021). A variety of critical frames, including critical psychology, Critical Race Theory (CRT), and TribalCrit are used to explore how psychology and education interact in the field of school psychology and how this impacts Indigenous peoples. Grounded theory approaches were adapted to incorporate Indigenous research design and ethics, including working with an Elder and a Community Advisory Committee to ensure Indigenous perspectives remained centred in the analysis. Participants at various career stages described training programs that included no Indigenous content and workplaces that emphasized assessment and testing for programming decisions rather than focusing on a holistic consideration of student needs. Participants were varied in their understanding not only of Indigenous worldviews but also the worldviews embedded in dominant psychology. Most participants were unable to provide a clear statement of what it might mean to decolonize their practice and most described some type of fear or anxiety as preventing them from doing more to incorporate Indigenous worldviews in their work. While participants varied in their reflective examination of their practice there appeared to be little awareness of their own DECOLONIZING SCHOOL PSYCHOLOGY subjective position within the profession. They did not make explicit links between Indigenous epistemologies and how that might impact pedagogical recommendations. Participants seemed to simultaneously place themselves outside the problem of colonization and outside the solution of decolonizing their practice. While participant reluctance to engage in further decolonization of their work can be explained in terms of being based in “precontemplation” fears in the trans-theoretical model of change (Prochaska et al., 2008), they are also symptoms of what Mawhinney (1998) describe as settler “moves to innocence” as an attempt to avoid responsibility and accountability. A key implication of this research for the future of school psychology is recognizing the lack of critical self-reflection among practitioners and helping them increase their awareness of their subjectivities and biases while overcoming their discomfort with the process of decolonization. Key words: school psychology, educational psychology, decolonization, Indigenous education, Indigenous research, psychology training
Open Access
Application of data-driven and physics-driven models in predicting vibratory responses of nonlinear dynamic systems
(Faculty of Graduate Studies and Research, University of Regina, 2024-06) Wang, Luyao; Dai, Liming; Mehrandezh, Mehran; Aroonwilas, Adisorn; Chen, Zengtao
The investigation of chaotic vibrations is essential for understanding the vibro-responses of engineering structures subjected to external excitations. This understanding is crucial for developing advanced strategies to control chaotic structural instability and sensitivity. Traditional methods for investigating chaotic vibration behavior rely on physics-based model establishment, where physical models are mathematically analyzed through complex calculations of differential equations. Although the development of analytical and numerical theories is relatively mature, the costly human labor required for feature engineering and high demands for expert knowledge in mathematical and physical domains limit its application in engineering fields to a certain extent. Therefore, this research aims to establish an innovative approach for predicting the chaotic responses of nonlinear models in the engineering field by proposing data-driven models to accomplish supervised learning regression tasks. The application of these proposed data-driven models in predicting chaotic responses of various nonlinear system models is conducted in a completely data-driven and non-intrusive manner. This thesis implements prediction tasks for chaotic vibrations of different types of nonlinear dynamic systems based on both physics-driven and data-driven models. These nonlinear systems serve as fundamental reference models and are widely applied in various engineering fields. Specifically, the physics-based investigations in this work focus on comparing the advantages of the developed P-T method over the 4th-order Runge-Kutta method in terms of accuracy and reliability. Additionally, studies on chaotic vibration prediction based on data-driven models are also carried out in this thesis. Three hybrid neural networks are proposed, and their architectures are thoroughly explained. The effectiveness and robustness of these models are sequentially enhanced. Specifically, their ability to handle chaotic sequences has evolved from considering temporal correlations to considering spatiotemporal correlations, and their capability to manage the length of inputs and outputs has progressed from fixed to variable. Besides the inherent advantages of data-driven investigation compared to physics-driven methods, the superior performance of the proposed data-driven models over conventional benchmarks in terms of training time and testing loss is quantitatively demonstrated. The continuous development of measuring equipment has facilitated easier access to substantial high-quality data. Thus, the findings of this research provide new insights into the investigation of chaotic responses and are valuable for analyzing and understanding chaotic vibrations with greater efficiency. The optimized results obtained in this research are expected to offer practically sound guidance for optimizing engineering structural design and enhancing performance when considering chaotic or nonlinear vibrations.
Open Access
Trust-aware virtual network embedding algorithms for wireless sensor networks
(Faculty of Graduate Studies and Research, University of Regina, 2024-06) Rezaeimoghaddam, Parinaz; Al-Anbagi, Irfan; Bais, Abdul; Zhang, Lei; Shahriar, Nashid; Yassine, Abdulsalam
Network virtualization (NV) in wireless sensor networks (WSNs) enables the utilization of their shared sensing capabilities. Efficient assignment of WSN resources to maximize the infrastructure provider’s revenue can be achieved by virtual network embedding (VNE) while considering the quality of information (QoI), quality of service (QoS), and wireless interference handling constraints. Improving the acceptance rate of VNE is essential because the more the virtual network requests (VNRs) can be mapped onto the substrate network, the more revenue they will generate for the infrastructure provider. However, the shared and complex nature of VNE exposes WSNs to security risks. In this thesis, we apply security constraints and address the trust-aware VNE problem with different algorithms to maximize the VNR acceptance rate while minimizing the cost for WSNs. This research includes four main objectives. In the first objective, we develop a novel centralized trust-aware virtual wireless sensor network (TA-VWSN) algorithm to improve QoI, QoS, and security and enhance the average network throughput, measurement error efficiency, and processing time when the trust attributes are assigned, making the VNE algorithm more practical. Since centralized algorithms suffer from scalability issues, in the second objective, we design a novel distributed trust-aware virtual wireless sensor networks (DTA-VWSN) algorithm by using multiagent systems (MAS) to scale these algorithms to network size. Our heuristic TA-VWSN and DTA-VWSN algorithms achieve a high-quality sub-optimal solution in a real-time manner, enabling us to investigate the tradeoff between solution quality and search time. However, the heuristic algorithms use manual embedding rules, which are incompatible with actual VNE situations. Therefore in the third objective, we develop a novel reinforcement learning-based (RL-based) trust-aware virtual wireless sensor network (RLT-VWSN) algorithm by employing a policy network and extracting attributes of the substrate nodes to get the mapping probability of each one. This algorithm is superior to heuristic algorithms in terms of VNR acceptance rate and cost. In the fourth objective, our first approach addresses node failures during mapping with a pioneering heuristic— the survivable trust-aware virtual wireless sensor networks (STA-VWSN) algorithm. It employs a failure recovery procedure, prioritizing nodes based on the technique for order of preference by similarity to ideal solution (TOPSIS) method. In the second approach, we enhance WSN substrate resilience against individual node and link failures through the development of the survivable and trust-aware reinforcement learning-based virtual network embedding for WSNs (SRLT-VWSN) algorithm. Utilizing the deep Q-Learning (DQL) method, this algorithm ensures end-to-end failure recovery and improves physical resource utilization intelligently.
Open Access
The quantile analysis of gene expression trajectory and quality control
(Faculty of Graduate Studies and Research, University of Regina, 2024-07) Lyu, Qi; Deng, Dianliang; Volodin, Andrei; Sardarli, Arzu; Venter, Jan-Paul; Yao, Yiyu; Yan, Guohua
In Chapter 2 of the thesis, Taguchi’s loss function in the multivariate case is reviewed and a straightforward and practical definition for the cost coefficient matrix is proposed. In order for the quality control process cost more realistic, the expected modified Taguchi’s loss function is applied on Hotelling’s T2 control chart based on a modified economic statistical design, and variable sampling interval (VSI) scheme is adopted. To obtain optimal design parameters, artificial bee colony (ABC) algorithm is utilized. By comparing our approach with previous routine design, it is concluded that redefining the cost factor makes the control system more sensitive to the process mean shift and the cost positive proportional to the process deviation, which is an important characteristic of good economic model. Temporal gene expression data can be used to characterize gene function, and gene expression trajectories showing different trends under various biological conditions appeals great interest of scientists. Most literature analyzed the gene expression trajectory by using traditional mean regression model, which does not perform well in practice due to the presence of non-normal distribution, potential outliers and heteroscedasticity in the data. Chapter 3 proposes a likelihood-based EM algorithm to estimate marginal conditional quantile of multivariate response in linear quantile regression framework, which studies the association between multivariate response and the explanatory variables across different quantiles. We assume that the error term is multivariate asymmetric Laplace distributed and derive the MLE of parameters and implement EM algorithm. The proposed approach is validated through simulation studies, and a real dataset application of 18 genes in P. aeruginosa expressed under 24 biological conditions is analyzed. In Chapter 4, in order to identify the similarity among the 18 genes in P. aeruginosa, the clustering tree for all genes is built by utilizing the Sz´ekely and Rizzo’s hierarchical e-clustering algorithm which is actually an extension of Ward’s minimum variance method. It is based on the empirical cluster distance between population distributions and is able to describe the hierarchical structure of multivariate data and classify the observations into some disjoint clusters. Moreover, similar to the ANOVA F test, the DISCO analysis partitions the total dispersion of observed response into between and within components and determines the test statistic. We conduct the pairwise DISCO tests among all gene expressions for the hypothesis of multi-sample equal distributions. Both methods illustrate that some gene expressions are highly likely from the same population.
Open Access
Community ecology of migratory bats in a northern sky island
(Faculty of Graduate Studies and Research, University of Regina, 2024-06) Green, Dana Maureen; Brigham, Mark; Baerwald, Erin; Somers, Chris; Buttigieg, Josef; Hurlbert, Margot; Fraser, Erin
Animal migrations are often motivated by the opportunity to exploit seasonal abundances of resources, a phenomenon particularly pronounced for species migrating to higher latitudes where seasonality is more extreme. Bats are the only mammalian order to have evolved flight, and three North American migratory bats are the long-distance migrating hoary (Lasiurus cinereus) and silver-haired bats (Lasionycteris noctivagans), and the regionally migrating little-brown Myotis bats (Myotis lucifugus). I describe a highly seasonal community of migratory bats in a northern “sky island” within the Cypress Hills of southern Saskatchewan, Canada, focusing on abundance trends, foraging behavior, niche ecology, and ecophysiology. By collecting data spanning 20 years, my first chapter describes that while long-distance migrating bats are experiencing population declines, the Cypress Hills currently has locally increasing abundances of hoary and silver-haired bats, likely driven by increased roosting habitat. Further in my second chapter, I found that three species of bat separate their ecological niches, allowing for current co-existence, but that silver-haired bats may experience competition with either the hoary or little-brown myotis. My final chapter describes the inter- and intra-specific differences of fur cortisol, a regulatory hormone often associated with stress. Notably, silver-haired bats exhibit elevated fur cortisol levels, but only in juveniles, suggesting it was transferred through their mothers milk while pups grew fur. Thus, female silver-haired bats likely have interactions within their environment causing increased cortisol circulation. Collectively based on my results, I postulate that long-distance migratory bats are disproportionally attracted to the Cypress Hills, and the local population of silver-haired bats may be experiencing increased inter- and intra- competition, resulting in heightened cortisol levels. Although each of the three bat species are seasonally abundant within the Cypress Hills, they are all currently experiencing population declines across their ranges. The environmental conditions hoary, silver-haired, and little-brown myotis bats face consist of highly seasonal resources in a relatively small area of land, while also experiencing habitat loss and increased risk during their annual migrations. My work highlights the importance of both long-term studies and datasets, and lays the foundation to continue to study the summer ecology of at risk species.
Open Access
Culturally relevant/responsive pedagogy in an EFL context: College English education in China
(Faculty of Graduate Studies and Research, University of Regina, 2024-07) Feng, Leyuan; Pirbhai-Illich, Fatmakhanu (Fatima); Massing, Christine; Boutouchent, Fadila; Sorensen, Michele; Dressler, Roswita
In China, College English, a core course in many university-level foreign language education, is a requirement for most non-English majors at the undergraduate level in China. In this doctoral research study, Ladson Billings’ (2014) culturally relevant pedagogy and Gay’s (2010) culturally responsive teaching was adapted for use in a college English course to develop student’s English language ability while enhancing intercultural awareness and competence. Guided by sociocultural theory (Vygotsky, 1986), this study employed action research methodology (Lewin, 1946; Stringer, 2014). The study took place at a comprehensive university in southwestern China. Participants consisted of 39 first-year students enrolled in the Chinese Language and Literature degree program. Data collection included the principal investigator’s self-reflective research journals, a critical friend’s classroom observations and interviews, student participant questionnaires, interviews and portfolios. After coding and thematic analysis (Norton, 2009; Saldana, 2016), the initial findings demonstrate that culturally relevant/responsive pedagogy increases student motivation, engagement, in-class participation, and interest in learning English because they found the content relatable to their own culture and therefore more meaningful. Additionally, most students indicated that they gained a deeper understanding of their own culture and cultivated cultural confidence, their English language skills improved, and their knowledge of the target language culture increased. In conclusion, an adapted culturally relevant/responsive pedagogy in college English education has the potential to respond to Chinese foreign language education policies and requirements and is worthy of in-depth exploration and active application. CRP IN AN EFL CONTEXT Key words: Culturally relevant/responsive pedagogy, English as a foreign language, College English.
Open Access
Quantification of dissolution and exsolution dynamics of gaseous solvents in crude oil systems under reservoir conditions
(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Dong, Xiaomeng; Yang, Daoyong (Tony); Gu, Yongan (Peter); Henni, Amr; Qing, Hairuo; Zeng, Hongbo
With a growing demand for fossil fuels, it is of a great importance to improve the oil recovery factor from both conventional and unconventional reservoirs. Among different enhanced oil recovery (EOR) methods, injecting gaseous solvents, including CO2, N2, flue gas, and alkane solvents, is considered as a more effective and efficient method in both light and heavy oil reservoirs, during which mass transfer is the key underlying recovery mechanism. In order to optimize the solvent injection method and achieve a higher oil recovery, it is of fundamental and practical importance to quantify both dissolution and exsolution dynamics of solvents in light and heavy oils under reservoir conditions. Firstly, a pragmatic method has been developed and applied to quantify the mutual mass transfer in different solvent(s)-light oil systems. Experimentally, diffusion experiments have been conducted for flue gas-light oil systems at constant pressures and temperatures. The dynamic liquid volume is monitored and recorded continuously during the experiments, while gas samples are collected at the beginning and end of each test to measure the gas fractions with gas chromatography (GC) analysis. Theoretically, by combining the Fick’s law and Peng-Robinson equation of state (PR EOS), the preferential and mutual diffusion between the flue gas and light oil can be quantified once the deviations between the measured and calculated parameters (i.e., dynamic swelling factor and gas composition) are minimized. Both individual diffusion coefficients for each gas component of a gas mixture in an oil phase and that of the extracted oil components in the gas phase are increased with pressure and temperature. Both the experimental and theoretical methods are modified and then extended to CO2/C3H8-heavy oil systems to quantify the mutual diffusivity between the gaseous solvents and heavy oil with the consideration of natural convection at high pressures and elevated temperatures or coupled with heat transfer process. Similarly, diffusion experiments are conducted with a PVT setup, during which the dynamic swelling factors of the heavy oil are measured continuously. Both oil and gas samples are collected at end of each test for oil compositional and GC analyses, respectively. The diffusivities of both solvents (i.e., CO2 and C3H8) in heavy oil and the extracted oil components in the gas phase are found to increase with pressure and temperature. Also, there exists an obvious extraction process from the oil to gas phases at elevated temperatures as light-medium components have been detected in the collected gas samples at end of the experiments. While coupling heat and mass transfer to determine the diffusivity of hot solvent in the heavy oil, thermal equilibrium is found to be achieved earlier than mass equilibrium. Combined heat and mass transfer will accelerate the oil swelling effect. Then, experimental and theoretical techniques have been developed to predict gas exsolution dynamics of CO2/CH4-heavy oil systems on the bubble level to reflect the physical behaviour of foamy oil. Experimentally, constant-composition-expansion (CCE) experiments have been performed in a sealed PVT system for a CO2-heavy oil system and a CH4-heavy oil system, respectively. Theoretically, the classical nucleation theory, population balance equations (PBEs), Fick’s law, and PR EOS has been integrated to predict the gas bubble number and size by reproducing the experimentally measured parameters (i.e., liquid volume and pseudo-bubblepoint pressure). It has been observed that both temperature and diffusivity of the gas component play an important role in the foamy oil behaviour. Compared with CO2, CH4 can induce a stronger and more stable foamy oil since more CH4 bubbles are dispersed in the oil phase.
Open Access
The hidden triad of cannabis influence
(Faculty of Graduate Studies and Research, University of Regina, 2024-07) Bojkovsky, Cynthia Dawn; Dupeyron, Bruno; Zarzeczny, Amy; Camillo, Cheryl; Mou, Haizhen; Novotna, Gabriela; Bear, Daniel
Description of the Problem In October 2018, the Government of Canada became the second country in the world to legalize non-medical cannabis, with the goal to promote better health and well-being amongst Canadians. To date, the ways in which young adults in Canada perceive and experience cannabis in this new legal context have been minimally explored and are not well understood. This research contributes important insights into how young adults in Saskatchewan perceive and understand their own health and well-being in relation to cannabis in a context of legal non-medical use. These findings are relevant for future policy and program developments in this area. Methods The objective of this study was to answer the primary research question “How do young adults perceive and experience cannabis use, in particular from a health perspective, in the context of Canada’s current policy frameworks?” This study applies constructivist grounded theory data collection and analysis techniques, guided by the work of Kathy Charmaz (2014). Data was collected through 10 in-depth interviews with young adults in Saskatchewan. The information was transcribed and thoroughly analyzed to transition from analytical findings to theoretical understanding. Secondary research questions addressed the relationship between cannabis related perceptions and experiences, influences shaping those perceptions and experiences, and the policy implications. Findings The main outcome from this study is entitled “The Hidden Triad of Cannabis Influence”, a grounded theory that explains how young adults perceive and experience cannabis within a legal non-medical and medical cannabis policy framework and an illicit market. Although the young adults who participated in this research tended not to outwardly identify policy and market factors as influencing their health and well-being, this theory substantiates the presence of these influences. The four main policy considerations emerging from this study include: • evaluate the short-term outcomes of non-medical cannabis legalization, including but not limited to input from young adults and qualitative research findings • develop a robust health literacy approach to promote public health objectives related to non- medical and medical cannabis use by young adults • improve supports in the health care system for medical use and misuse of cannabis to promote harm reduction • take additional measures to mitigate the illicit market for cannabis The results of this study offer preliminary evidence about how young adults perceive and experience their own health and well-being within a context of legal non-medical cannabis. Keywords Cannabis; marijuana; legalization; young adults; grounded theory; health policy; perceptions
Open Access
L'insécurité linguistique chez les élèves d'immersion française en Saskatchewan
(Faculty of Graduate Studies and Research, University of Regina, 2024-05) Adedeji, Olushola Joseph; Akinpelu, Michael; Aito, Emmanuel; Poplyansky, Michael; Magnan, André; Sterzuk, Andrea; Wernicke, Meike
Although French immersion program has been quite successful over the last few years in Saskatchewan due to the number of students enrolled in the program, many students in the program demonstrate a lack of confidence in expressing themselves in French. This PhD thesis attempts to provide a better understanding of linguistic insecurity among French immersion students in Saskatchewan while drawing on the perspectives of students and teachers; perspectives such as these are not clearly reflected in most studies on linguistic insecurity among French immersion students in Canada. The qualitative and quantitative data collected from students and teachers lead to the conclusion that, generally, most French immersion students in Saskatchewan have a positive attitude toward French language, and they consider their experience in the program a positive one. However, despite their enviable level of proficiency in French, some of them are not always confident to express themselves in French in certain circumstances, especially outside of a well-structured French class. This lack of confidence does not necessarily stem from a low level of proficiency in French but rather from the lack of opportunities to interact in the language. This is exacerbated by native-speaker ideologies as well as other factors such as the preconceived notion that French is only useful at school, the negative judgment others have of their language skills. As a result, students do not appreciate their enviable level of proficiency in French, make less effort to speak it and display less confidence in identifying as bilingual and as part of the French-speaking world. This situation negatively impacts the achievement of the objectives and the maintenance of the principles of the French immersion program, thus affecting the development and promotion of French in Saskatchewan. According to this study, to alleviate linguistic insecurity among students, it is imperative to focus, among other things, on creating several opportunities for students to interact in French and on explicitly teaching French grammar and vocabulary through an enjoyable approach. Key Words: Sociolinguistics, French immersion, linguistic insecurity, language norms, linguistic variation, sociolinguistics for change, French as a second langue, second language acquisition, French immersion ideologies
Open Access
Impact of an online discussion forum on self-guided internet-delivered cognitive behavioural therapy for Canadian public safety personnel: A randomized trial
(Faculty of Graduate Studies and Research, University of Regina, 2023-10) McCall, Hugh; Hadjistavropoulos, Heather; Sharpe, Donald; Carleton, R. Nicholas; Jones, Nicholas; Böttcher, Johanna
First responders and other public safety personnel (PSP) are at elevated risk of experiencing potentially psychologically traumatic events, mental disorders, and barriers to accessing mental healthcare. Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for various common mental disorders. Therapistguided ICBT is more effective than self-guided ICBT, but self-guided ICBT is easier to implement on a large scale. Designing self-guided ICBT to be more engaging for users has been recommended to improve engagement and outcomes. One way to engage users is to provide them with access to an online discussion forum. Self-guided ICBT interventions that have included online discussion forums have demonstrated excellent treatment outcomes, comparable to those of guided ICBT, but there is a need for research experimentally testing the impact of adding online discussion forums. The current study objectives were to evaluate a transdiagnostic, self-guided ICBT program tailored for PSP, explore whether a therapist-moderated online discussion forum impacts outcomes, and analyze participant feedback to inform future efforts to implement forums in ICBT. The current study consisted of a randomized trial (n = 107) with two conditions, both of which involved an 8-week, transdiagnostic self-guided ICBT course tailored for Canadian PSP. In one condition, but not the other, the ICBT course included a therapistmoderated online discussion forum. We administered several self-report measures during eligibility screening and at 8 and 20 weeks post-enrollment. Primary outcomes included changes in symptoms of major depressive disorder, generalized anxiety disorder, and posttraumatic stress disorder. Secondary outcomes included treatment satisfaction, treatment engagement, patient-program alliance, and changes in health service use, resilience, and subjective wellbeing. We compared treatment outcomes across the two conditions using multilevel modeling. We used qualitative analyses to further examine written comments related to treatment satisfaction and participants’ experiences with the online discussion forum. Across conditions, most participants accessed at least four of the five lessons of the ICBT course (n = 59, 55.1%) and completed post-treatment questionnaires at 8 weeks (n = 83, 77.5%) and 20 weeks post-enrollment (n = 73, 68.2%). Participants in both conditions who reported clinically significant symptoms at pre-treatment reported large and statistically significant reductions in symptoms (ps < .05, ds > 0.97). Participants also evidenced good treatment satisfaction and engagement. There was no evidence of group differences on any treatment outcomes, and most outcomes were comparable to those of therapist-guided ICBT tailored for PSP. However, 30.0% of prospective participants in the present study either failed to access the ICBT course or withdrew from the study, compared with only 5.7% for therapistguided ICBT. Participants created only nine posts in the online discussion forum. Qualitative analyses revealed that the forum had both strengths (e.g., it helped some participants feel less alone) and limitations (e.g., some participants disliked the relatively low level of activity). The current results support continued research on and implementation of self-guided ICBT for PSP and other groups. Results also suggest a need for further research to determine how online discussion forums should be structured and implemented in self-guided ICBT and to clarify their impact on outcomes.
Open Access
Multi-level energy-environmental-economic modeling for supporting low-carbon transition of power systems under uncertainty
(Faculty of Graduate Studies and Research, University of Regina, 2022-11) Zhang, Xiaoyue; Huang, Gordon; Young, Stephanie; Zhu, Hua; Yao, Yiyu; Qin, Xiaosheng
To combat climate change, the low-carbon transition of electricity systems is of critical significance. Such transition is a complex and long-term process, involving many social, economic, environmental, technical and political factors, and requires a complete analysis for every aspect of the transition pathways. In this dissertation, low-carbon transition strategies of electricity systems were studied from three levels. A set of identification, optimization, and simulation models were developed to facilitate the analysis. For the efforts made at the technical level, the necessity and feasibility of introducing an emerging low-carbon power generating technology (i.e., SMRs) have been studied, with a focus on suitable site selection and environmental impact analysis. For the power systems level, optimized low-carbon transition pathways have been identified, taking into account the effects of multiple uncertainties and the associated risks. In addition, given the tight ties that exist between socio-economic systems and power systems, corresponding impacts of the transition strategy made in the second level on socioeconomic systems have been explored, such that the performance of the entire economy can be assessed. The major contribution of this research is the development of a set of innovative models to aid in the management of power system transition under uncertainty. Overall, the proposed models outperformed the previous modeling approaches due to their advantages in complexity characterization, uncertainty representation, impact analysis, and policy formulation. In detail, the proposed models and related contributions are: (1) climate-oriented SMR site recognition model (CSSR), which is capable of taking long term variation of climate conditions into consideration while conducting siting studies; (2) SMR-induced environmental input-output model (SEIOM), which can quantify contributions of having an emerging power-generating technology as an alternative energy supplier to emission mitigation and related impacts on other sectors; (3) stochastic multistage lifecycle programming model (SMLP), through which detailed environmental and economic profiles of each power generation technology were systematically investigated within lifecycle frameworks and were considered in power system optimization modeling, such that the robustness of the resulting decision support can be enhanced; (4) coupled non-deterministic optimization and mixed-level factorial analysis model (NOMFA), which is an attempt to integrate the system optimization methods with mixed-level factorial design under various uncertainties, such that effects of various external interferences and their interactions on the systems can be investigated; (5) nondeterministic optimization-driven factorial CGE model (NFCGE), which is an integration of “economy-wide” equilibrium models and “technology-rich” energy system optimization approaches, and can help investigate the responses of various economic sectors to alternative transition strategies as identified through the optimization efforts. The developed models were applied to a number of Canadian and Chinese cases to demonstrate the applicability and superiority. The results can assist decision-makers in identifying the most efficient and feasible low-carbon transition pathways for power systems and in achieving a more balanced energy-environment-economic structure.
Open Access
Role of Nudix-Hydrolase ASMTL in Modulating Mitochondrial Biogenesis of Cancer Cells
(Faculty of Graduate Studies and Research, University of Regina, 2021-05) Amin, Shahreen Tina; Babu, Mohan; Fitzpatrick, Dennis; Suh, Dae-Yeon; Weger, Harold; Kumar, Ashok
Cancer cells have enhanced DNA biosynthesis, rendering them susceptible to nucleotide modifications that enter the cellular nucleotide pool during repair or DNA degradation. These modified nucleotides can then be incorporated into newly synthesized DNA, resulting in random mutations or, when overwhelming into DNA damage, culminating into apoptosis, which is the desired effect of anti-cancer chemotherapy. Human cells contain nucleotide sanitation enzymes like ASMTL, which prevent incorporating the non-canonical nucleotides into newly synthesized DNA by removing them from the nucleotide pool, thereby relieving cancer cells from proliferative stress-induced mutations and apoptosis, representing an attractive target for anti-cancer chemotherapy. To identify ASMTL as a target for anti-cancer treatment, we investigated the ASMTL requirement for cancer survival in human cancer cell lines and patients, where ASMTL depletion decreased survival. This decrease in cell survival correlated with 14-3-3 interaction-dependent mitochondrial localization of ASMTL. Analyzing mitochondrial function suggests that ASMTL is imperative in the TP53 dependent BAX-BCL2 pathway, which is turned on by inefficient repair of mtDNA damage. Furthermore, after screening 2040 compounds, we identify small molecules TFBQ and TFHQ as ASMTL inhibitors that potently and selectively engage the ASMTL protein after occupying putative ASMTL MAF active site and impeding ASMTL-14-3-3 interaction. Finally, ASMTL is validated as an anti-cancer target in vivo where ASMTL knockout or inhibition triggers apoptosis and decreased metastasis in xenografts. This study collectively exemplifies the non-oncogene addiction concept for cancer treatment and validates ASMTL as phenotypically lethal to carcinomas.
Open Access
Cardiac cycle timing intervals in acute COVID-19 and recovered COVID-19 with sustained symptoms
(Faculty of Graduate Studies and Research, University of Regina, 2022-06) Singh, Jyotpal; Neary, Patrick; Bardutz, Holly; Bhagaloo, Lanishen; Mang, Cameron; Buttigieg, Josef; Eves, Neil D.
Research is available to show that COVID-19 can result in both acute and sustained cardiac damage. Acute cardiac damage may be due to elevated inflammatory responses and can result in ischemia, which can lead to impairments in the cardiac cycle timing events. The purpose of this project was threefold: 1) to characterise cardiac cycle timing intervals in patients with COVID-19, 2) to understand the mechanisms that compromise cardiac function in post-acute COVID-19 syndrome (PACS)/long COVID, and 3) to identify unique cardiac dysfunction which can occur due to COVID-19 as compared to cardiac and respiratory disease. First, case studies showed that daily observation of cardiac function provided detailed information about the overall dynamic changes by which cardiac dysfunction occurs, and thus can be beneficial study on a case by-case basis, day-to-day during acute infection. The literature review supports the findings of altered cardiac mechanics and suggests that right ventricular dysfunction, along with global longitudinal strain and diastolic dysfunction are common findings in patients with PACS/long COVID, and a more severe acute myocardial injury during the index hospitalization appears to exacerbate cardiac function on follow-up. Finally, a Kruskal-Wallis ANOVA showed that participants with COVID-19 and sustained symptoms present with elevated systolic time and decreased IVCT in comparison to acute COVID-19, and those with respiratory and cardiac disease. These are reflected by decreases in heart, diastolic, and systolic performance indices (HPI, DPI and SPI, respectively), thereby showcasing a unique cardiac dysfunction in patients with sustained symptoms from COVID-19. Future research must consider the details of cardiac complications during the acute infection period and relate this to the cardiac function in patients with long COVID during a mid- and long-term follow-up.
Open Access
Efficacy of an Internet-delivered self-compassion intervention in preventing depressive relapse and recurrence: A randomized controlled trial in a clinical sample
(Faculty of Graduate Studies and Research, University of Regina, 2023-12) Yu, Kwan Tsz; Beshai, Shadi; Asmundson, Gordon; Hadjistavropoulos, Heather; Martin, Ron; Dozois, David J.A.
Depression is a prevalent and burdensome mental health condition. Unfortunately, depression is chronic and recurrent, with a lifetime average of four to five episodes. Although evidence supports the efficacy of self-compassion interventions for a range of psychological disorders (Ferrari et al., 2019), research on scalable forms of compassion-based interventions for recurrent depression remains scarce. The primary purpose of this two-arm randomized controlled trial (RCT) was to examine the efficacy of a 6-week internet-delivered, self-directed self-compassion intervention in preventing depressive relapse and recurrence over a 12-month period in a clinical sample of adults with a history of depression. The efficacy of the intervention was tested against a self-reflection active control condition. In addition to examining differential relapse/recurrence rates, the RCT compared changes in the primary outcome of depressive symptoms (PHQ-9), and secondary outcomes of self-compassion (SCS), mindfulness (FFMQ-15), decentering (EQ-D), and fear of self-compassion (FCSS) across conditions and time. A total of 158 participants meeting eligibility criteria (87% identifying female; M number of prior depressive episodes = 2.88 [SD = 1.82]) were randomized into the self-compassion (SC; n = 80) intervention condition or self-reflection (SR; n = 78) active control condition. All participants completed primary and secondary outcome measures at baseline, weekly throughout the 6-week intervention period, at post-treatment, and at each of four followups (at 3-, 6-, 9-, and 12-month post-randomization). Participants also completed a phone interview at each follow-up to determine relapse/recurrence status. Depressive episodes were assessed by a structured interview. Kaplan-Meier survival analyses were conducted to compare rates of depressive relapse/recurrence between the two conditions across the trial period. Cox proportional hazards regression analyses were conducted to examine the effects of predictors on time until relapse/recurrence. Multilevel modeling and mixed model analysis of variance were conducted to examine differential changes in primary and secondary outcomes between the two conditions. Contrary to primary hypotheses, survival analysis revealed no significant differences in relapse/recurrence rates between SC participants (relapse rate = 33%) and SR participants (relapse rate = 43%) across the 12-months trial period, χ2(1) = .35, p = .56. Number of past depressive episodes and baseline fear of self-compassion predicted time until relapse/recurrence in an exploratory survival analysis; greater number of past episodes and higher levels of fear of self-compassion were associated with a higher likelihood of relapse. Further, SC participants did not report significantly greater reductions in depressive symptoms, nor significantly greater increases in mindfulness and decentering compared to SR participants. However, SC participants reported significantly greater increases in self-compassion and significantly greater decreases in fear of self-compassion compared to SR participants across the trial period. Results revealed a main effect of time on all outcome measures; participants in both conditions reported significantly lower distress across time. The current findings support self-directed self-compassion training as a feasible approach to cultivating protective and reducing risk factors associated with recurrent depression. Self-compassion training through an internet-delivered self-directed program may be appropriate for use as an adjunct to more established evidence-based treatments specifically targeting relapse in depression. Keywords: recurrent depression, relapse/recurrence, self-compassion, mindfulness, decentering, fear of self-compassion, compassion-based intervention, RCT
Open Access
Geochemical modeling of diagenesis, hydrothermal alteration, and unconformity-related uranium mineralization in the Athabasca Basin, Saskatchewan, Canada
(Faculty of Graduate Studies and Research, University of Regina, 2024-01) Wang, Yumeng; Chi, Guoxiang; Qing, Hairuo; Robbins, Leslie; Jia, Na; Yang, Jianwen
Unconformity-related uranium (URU) deposits in the Athabasca Basin were interpreted to have formed through interactions between oxidizing basinal fluids and reducing basement-derived fluids or basement lithologies under diagenetic-hydrothermal conditions. However, there is controversy regarding whether U is ultimately derived from the basin or the basement, fluid flow mechanisms responsible for metal leaching and transport, and deposition mechanisms of ores. This study uses geochemical modeling to: 1) determine fluid flow patterns responsible for U leaching and transport in the Athabasca basin; 2) recognize critical factors controlling ore deposition near the unconformity intersected by basement faults; and 3) constrain metal sources, fluid migration pathways, and ore precipitation mechanisms for U and associated elements, including Ni, Co, and As, which are anomalously enriched within some URU deposits. Petrographic observation on four drill cores indicates that the top of the sandstone succession below a mud-rich aquitard is characterized by extensive quartz overgrowths, whereas the basal part contains little cement and shows extensive dissolution features. Reactive transport modeling indicates that such a quartz cementation-dissolution pattern can be produced only if the sandstones are sufficiently permeable and thick so that the Rayleigh number exceeds the critical value for thermal convection. The results indicate that thermal convection did occur in the Athabasca Basin and may have facilitated the large-scale circulation of diagenetic fluids to leach and transport U within sandstones. Reactive transport modeling further shows that significant URU mineralization occurs at a fault-unconformity intersection only if thermal convection and basin- basement fluid mixing take place concurrently. If there is no thermal convection in the basin, only sparse U mineralization occurs along the unconformity. If insufficient amount of reducing fluid is provided from the basement fault, no significant U mineralization occurs either. Furthermore, no significant U mineralization occurs if the U concentration in the basinal fluid is low. It is concluded that the formation of URU deposits is the result of coupling of three critical factors: high-permeability sandstone favoring thermal convection in the basin, ample supply of reducing fluids along reactivated basement faults, and abundant U-rich basinal fluids in the basin sequences. Thermodynamic modeling indicates that significant amounts of U can only be transported by highly oxidizing fluids, whereas Ni, Co, and As can be co-transported with U in the same highly oxidizing fluids, or in moderately oxidizing fluids without U. Reaction path modeling further shows that uraninite precipitates before Ni-Co arsenides and sulfarsenides, when ore fluids interact with basement lithologies or mix with reducing fluids. These results confirm the ore precipitation sequences observed in typical URU deposits, and the significance of fluid mixing in ore deposition, and provide theoretical support for crystalline basement rocks as the primary Ni-Co-As source. The thesis concludes that the basin is the primary U source, and thermal convection is vital for leaching of U from the basin and its transport to mineralization sites; the spatial-temporal coupling of thermal convection and basin-basement fluid mixing is key for U deposition and accumulation at fault-unconformity intersections; Ni, Co, and As were leached from basement rocks by percolating basinal brines, and different patterns of fluid flow and fluid mixing result in the co-mineralization of U, Ni, Co, and As in certain deposits, but not in others.
Open Access
Application of density functional theory and machine learning in the prediction of efficient catalysts for the oxidative coupling of methane with reduced CO2 production at low temperature
(Faculty of Graduate Studies and Research, University of Regina, 2024-03) Ugwu, Lord Ikechukwu; Ibrahim, Hussameldin; Henni, Amr; Shirif, Ezeddin; Widdifield, Cory M.; Castaño, Pedro
The oxidative coupling of methane (OCM) remains a promising means for the production of ethylene. Though high temperatures of 900 oC and above lead to increased conversion of methane, at higher temperatures, the OCM reaction tends to favour a competing reaction that leads to the production of COx product. This thesis focuses on the generation of catalyst component electronic properties via density functional theory (DFT) and the analysis via machine learning (ML) techniques of the combination of the DFT-computed electronic properties and high-throughput experimental data comprising 12708 data points. The DFT data includes the catalyst components' bandgap, Fermi energy and magnetic moment. Variations of a dataset comprising experimental conditions, experiment performance and electronic catalyst properties were used to build a dataset for data modelling and analysis as well as ML analysis for the prediction of CO2 yield, C2H4 yield C2H6 yield, and CH4 conversion. With the aid of multi-linear regression models, Rh, Pt, Ru and Ir were found to be new catalyst promoters that enhance catalyst performance in OCM, particularly with improved methane conversion. A minimum of 58 new bimetallic combinations and 2784 unique catalytic materials with minimum CH4 conversion at 700 oC of 38.5% were identified and proposed as effective catalysts for OCM reaction, an improvement on the 36% CH4 conversion limit from previous studies. The Rh-Li3VO4/SBA15 and Ru-BaZrO3/SBA15 have been proposed as efficient catalysts for the OCM reaction with a predicted C2y of 30% and 29%, respectively. In comparing predictive model using a dataset containing a combination of catalyst electronic properties, deep neural networks (DNN) configured as deep feed-forward networks with back-propagation, along with random forest regression (RFR), support vector regression (SVR) and extreme gradient boost regression (XGBR), were compared on the basis on their mean-absolute-error, mean-squared-error and coefficient of determination for the prediction of reaction outcomes including ethane yield, ethylene yield, carbon dioxide yield and methane conversion (C2H4y, C2H6y, CO2y, CH4_conv, respectively) and C2y (a combination of C2H4y and C2H6y). The inclusion of electronic properties of the catalyst components into the dataset improved the performance of the models by approximately 10% compared to a dataset with only reaction conditions. RFR models had better accuracy compared to other modeling techniques, with an average R2 of 0.98 for the predictive models of all five reaction outcomes. The mean squared error and mean absolute error of the RFR models were from 0.12 to 9.03 for MSE and 0.21 to 2.02, respectively. The order of performance of the modeling techniques was RFR > XGBR > SVR > DNN. The order of data fit for the labels for the given modeling techniques was C2H6y > C2H4y > C2y > CO2y > CH4_conv. In the analysis of model feature impacts to identify descriptors for catalytic activity in OCM reactions, it was observed that the Fermi energies of the catalyst promoter, its atomic number and the bandgaps of the bimetallic oxide and the catalyst support emerged as effective descriptors. Specifically, in relation to the C2y predictive model, C2y increases with an increase in dataset features, including the number of moles of the alkali/alkali-earth in the metallic oxide, atomic number of the catalyst promoter and Fermi energy of the promoter and just relatively in the case of temperature, suggesting a highly non-linear relationship between C2y and temperature. It, however, reduces with an increase in the bandgap of the active metal oxide and the methane-to-oxygen ratio. Using the RFR, the Fermi energy of the promoter had a 4.31% impact on the model, while its atomic number had 6.24%, the number of moles of the alkali/alkali-earth in the metallic oxide was 13.69%, and temperature was 33.70% on the C2y predictive model. catalysts with active metal oxides with lower bandgap energy and promoters with magnetic moments may not be as effective as OCM reaction catalysts with less ferromagnetic properties and higher bandgap energy.
Open Access
Improving applicability of the non-monotone unified estimate for missing data
(Faculty of Graduate Studies and Research, University of Regina, 2023-11) Thiessen, David Luke; Zhao, Yang; Bae, Taehan; Deng, Dianliang; Yao, Yiyu; Variyath, Asokan Mulayath
In applied statistics missing data are a common problem. Performing a "complete case analysis" by removing individuals with missing data causes a loss of statistical power and can cause non-response bias. Inverse probability weighting is one method used to avoid non-response bias. However, when some individuals have partially observed data inverse probability weighting has only a limited ability to use this data. The unified approach (Zhao and Liu, 2021) is a modification of inverse probability weighting that uses "working models" to extract information from individuals with partially observed data. When the probability an individual has missing data can be accurately modeled but the distribution of the data is difficult to model the unified approach is an attractive option. In this thesis we review the theory of the unified estimate and its application to the Cox proportional hazards model for survival data. We present a new R program which can be used to easily fit the unified estimate for generalized linear models or Cox proportional hazards models. Possible hypothesis tests for the fit of the unified estimate and directions for future research are suggested.
Open Access
Partial wave analysis of Neutral b1 Meson at GlueX
(Faculty of Graduate Studies and Research, University of Regina, 2023-09) Suresh, Karthik; Papandreou, Zisis; Teymurazyan, Aram; Mack, David J.; Lolos, George; Meagher, Karen; Perrino, Roberto
A long-standing goal of hadron physics has been to understand how the quark and gluon degrees of freedom that are present in the fundamental QCD Lagrangian manifest themselves in the spectrum of hadrons. The GlueX experiment at JLab contributes to the global spectroscopy program through studies of the mesons produced using a beam of 8-9 GeV linearly polarized photons. This experiment focuses on the exploration of the light-quark domain, potentially accessing hybrid mesons with exotic JPC quantum numbers in photoproduction reactions. Recent Lattice QCD calculations predict that the lightest exotic π1(1600) decays primarily to a b1 system and can be experimentally accessed through the dominant decay b1 → ωπ0. In this dissertation, direct production of the b1 meson γp → b1p where the axial-vector meson b1(1235) decays to ωπ0, is studied in detail. Results of Partial Wave Analysis (PWA) on the photoproduction of the b1(1235) meson system are shown, with emphasis on the extraction of D-wave to S-wave ratio (termed dsratio), which is a characteristic property of this meson and this coupling has been predicted by Lattice QCD calculations. The dsratio does not depend on the production mechanism nor on features such as the momentum transfer (|t|) or the polarization of the photon beam. PWA in the mass range between 1.0 − 2.0 GeV was carried out in bins of 80 MeV, and three momentum transfer, |−t|, ranges. The analysis procedure was validated using Monte Carlo simulated data to be free of any potential biases. Fits describe the five characteristic angles in the two-plane b1 → ωπ0 → π+π−π0π0 decay. An advanced model selection strategy used the metrics of Likelihood Ratio Test and information criteria Akaike Information Criterion and Bayesian Information Criterion, and demonstrated that the [JP ](ϵ) state of [1+](+) is the most dominant wave which concludes that the photoproduction of b1 is found to proceed through unnatural parity π0 exchange. Additionally, the [1−](+) wave without resonant structure was found to be the second strongest wave. This is consistent with results in the literature from a complimentary experiment that was run more than two decades ago, with the current work exceeding the statistical precision by at least an order of magnitude and systematic uncertainty being competitive with previous measurements. Evidence of the need for higher waves in the higher mass region was found and is in agreement with past results. Contributions from individual m projections for the photoproduction of ωπ0 corresponding to the [1+] as a function of |t| are extracted and presented for the first time in this dissertation. The dsratio was extracted under the condition of a fixed D − S phase (termed dphase) and was shown to be constant as a function of variables. This was expected, although with a lower value than theoretical calculations for the highest |t| bin, which will be investigated in future by others. A thorough set of systematic variations were performed to evaluate the systematic uncertainties. The study concluded that the largest error comes from the choice of the waveset used to describe the data. Future studies should include the variation of dphase. Finally, service contributions were made towards the gain calibration of the Barrel Calorimeter detector built by the Regina group. Additionally, for a period of eight months, a pioneering study was carried out using Artificial Intelligence towards the dimensional and positional optimization of a detector, for the Electron-Ion Collider (EIC) facility under the proto-collaboration named ECCE. The results of this study are summarized in this dissertation.
Open Access
Advanced approaches to ruin probability and novel extensions of Hoeffding Inequalities in insurance mathematics
(Faculty of Graduate Studies and Research, University of Regina, 2024-01) Soufiani, Elham; Volodin, Andrei; Deng, Dianliang; Sardarli, Arzu; Yao, Yiyu; Hatefi, Armin
In the ever-evolving domain of risk theory, understanding the intricate relationships between ruin probability, risk management, and the complexities of financial mathematics has never been more imperative. This thesis provides a comprehensive exploration into the nuances of ruin probability and its critical importance in the modern financial landscape. By delving deep into the mathematical intricacies, the study generalizes Hoeffding inequalities for random variables belonging to an extended acceptable class. This generalization is pivotal, leading to the establishment of the minimum premium rate. The thesis achieves this through the construction of an exponentially decaying upper bound for the ruin probability, built upon the foundational concepts of Hoeffding’s generalization. Furthermore, the research draws inspiration from seminal works in the field, paying homage to pioneers such as Filip Lundberg and Harald Cramér. While the contributions of these stalwarts have been immense, the contemporary challenges of the financial world demand a fresh perspective and novel methodologies. To this end, the study encapsulates the interdependencies between various financial elements, the importance of understanding negatively dependent or extended acceptable random variables, and the criticality of large deviation inequalities. Moreover, the synthesis of past methodologies with the latest techniques has enabled a more comprehensive understanding of exponentially decaying inequalities. The thesis provides a thorough literature review, chronicling the evolution of thought in the realm of risk theory, bridging the gap between historical foundations and current advancements. In conclusion, this thesis stands as a testament to the importance of rigorous mathematical frameworks in understanding and navigating the complexities of risk management in today’s volatile financial ecosystem.
Open Access
Discretization of nature-inspired techniques for combinatorial problems
(Faculty of Graduate Studies and Research, University of Regina, 2023-11) Sadeghilalimi, Mehdi; Mouhoub, Malek; Louafi, Habib; Shahriar, Nashid; Volodin, Andrei; Bagheri, Ebrahim
Scientists across various domains like scheduling, computational biology, and machine learning face constraint-solving and optimization problems. Classical systematic and mathematical methods often fall short of providing suitable solutions for such complex problems, leading to the introduction of metaheuristic algorithms. These algorithms exhibit diverse characteristics and can effectively address specific optimization problems. The primary motivation is to develop robust metaheuristics that can efficiently handle scaling problems. However, one challenge with metaheuristics is their immature convergence. In the context of Constraint Satisfaction Problems (CSPs), a framework applicable to numerous real-world problems, metaheuristics play a significant role. To address these objectives and challenges, this thesis investigates the applicability of metaheuristics, including the Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Water Cycle Algorithm (WCA). More precisely, we propose a discrete version of nature-inspired techniques for solving the Electricity Technician Dispatch Problems (ETDP), the Nurse Scheduling Problem (NSP), and the Task Scheduling Problem in Mobile Cloud Computing. We also propose a discrete version of WOA for Type 2 Diabetes Diagnosis. Experimentation showcases the efficiency of the proposed techniques in finding a good trade-off between running time and the quality of the solution returned.