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Navigating Diversity Recruitment Across Canadian Police Forces
No full textThis research employed a qualitative approach within a post-positivist and critical realism framework to investigate the barriers and facilitators of diversity recruitment within Canadian police organizations. Specifically, the study was designed to identify systemic and historical biases within recruitment practices, as well as the challenges that police recruiters observed marginalized communities facing in accessing policing careers. The Enhanced Critical Incident Technique (ECIT) was used to conduct a series of semi-structured interviews with a sample of six recruiters who are currently or were formerly involved in recruiting police officers across Canada. Data analyses focused on categorizing factors that influence effective diversity recruitment and the proposed solutions to overcome existing barriers. Helping factors included intentional community engagement efforts, organizational equity, diversity, and inclusivity (EDI) commitment and training, and diverse representation within recruitment teams. Hindering factors centered on outdated or biased assessment tools, community mistrust rooted in historical harms, and a lack of sustained investment in diversity initiatives. Wish list items highlight the need for modernized assessment practices, national recruitment frameworks, and long-term mentorship and outreach programs. The findings are contextualized within the broader literature on EDI in law enforcement and informed several recommendations, such as updating entrance assessments to reflect core policing competencies, expanding outreach to marginalized communities through culturally responsive strategies, and ensuring recruitment teams reflect the diversity of the populations they serve
T7-like Phages Infecting Native Rhizobia: Isolation, Host Range, and Genomic Insights
No full textThe competitive dynamics between native and inoculant rhizobial strains in soil can negatively affect the success of nitrogen-fixing symbioses in legumes. This study aimed to isolate bacteriophages capable of selectively infecting and lysing native rhizobia, thereby reducing competition and improving the chances of efficient, inoculant strains to establish symbiosis. Rhizobial strains were isolated from soil and nodule samples and identified using 16S rRNA, recA, and atpD gene sequencing. Plasmid profiling was conducted using Eckhardt gels. Bacteriophages were extracted from the same soils, isolated using the double-layer agar method, and characterized through transmission electron microscopy (TEM), restriction enzyme digestion (EcoRI, Tru1I, and MboI), and whole-genome sequencing. Several T7-like phages were identified, including both lytic and temperate types. Notably, some lytic phages demonstrated selective infectivity toward native rhizobia—particularly strains closely related to Rhizobium leguminosarum, R. johnstonii, and R. trifolii—while showing no infectivity against common laboratory strains. These findings support the potential use of lytic phages as biocontrol agents to reduce native, less-effective rhizobia in the rhizosphere, thereby enhancing the performance of engineered inoculant strains. Future research should focus on evaluating these phages' effectiveness and ecological safety in natural soil conditions
Firefighter Mental Health and Psychological Wellbeing at Work: A Mixed Methods Protocol
No full textThe opioid overdose and drug poisoning crisis has created a drastic shift in the work of firefighters in North America. With record high death rates among people who use drugs, all municipal services have been mobilized to respond to a complex social challenge. Firefighters provide essential services that include responding to overdoses and drug poisonings, particularly when Emergency Medical Services (EMS) personnel are not available. In Alberta, EMS faces significant call volumes, and calls relating to drug poisonings and mental health issues are being increasingly diverted to firefighters. While firefighters are trained as first responders to provide basic life support, mental health and addiction issues are outside their traditional remit. Learning more about how to support firefighters as they respond to mental health and addiction calls can prevent mental injuries among firefighters, reduce job-related stress, and promote retention across the firefighter workforce
Physiological High-Frequency Oscillations in Scalp EEGs Change During Brain Maturation
No full textHigh-frequency oscillations (HFOs), occurring between 80-1000 Hz, were first identified only three decades ago. Since then, physiological HFOs have been implicated in learning, memory and motor function, while epileptic HFOs have been associated with epileptogenic tissue. Many studies have shown that HFO activity correlates with seizure frequency, severity, and surgical outcomes. However, distinguishing physiological from epileptic HFOs remains challenging due to their overlapping frequency ranges and similar morphologies. Little is known about how physiological HFOs change throughout typical brain development. Without a clear understanding of normal developmental patterns, it is difficult to determine which HFOs are truly physiological and which may be pathological. This thesis aims to characterize normative developmental changes in physiological HFOs across age, brain region and sex. Using a dataset of 244 scalp EEG recordings from
developmentally typical children, we found that HFOs follow a structured developmental trajectory, differ by sex and vary regionally across different stages of maturation. These findings were used to generate a reference atlas describing typical HFO occurrence rates per minute. This atlas serves as a foundational tool for understanding physiological brain development and for distinguishing normal HFO activity from epileptic patterns. Moreover, this work also highlights the feasibility of automated HFO detection from scalp EEGs. The use of non-invasive methods opens the door to larger-scale studies and broader applications beyond epilepsy
Using Genome Sequencing and Advanced Technologies to Diagnose Individuals with Rare Diseases
No full textAlthough individually rare, rare diseases (RDs) are estimated to impact up to 1 in 12 Canadians, and approximately 80% are estimated to be genetic. While the clinical adoption of exome sequencing has seen great success, over 50% of individuals with an RD remain undiagnosed after standard of care genetic testing. Short-read genome sequencing (GS) and additional technologies such as long-read whole-genome sequencing (LR-WGS) and RNA sequencing (RNAseq) offer improved detection of all forms of genetic variants across the genome, however they are currently primarily limited to translational research. The primary goal of this thesis was to develop and optimize an approach to using GS, and subsequent RNAseq and LR-WGS, to diagnose individuals with RDs. I specifically focused on the diagnosis of a cohort of 18 individuals for whom previous genetic testing identified a single heterozygous, known pathogenic variant in an autosomal recessive disease gene, felt to be a fit for their clinical presentation. Experimental validation and additional clinical testing were also performed when necessary to prove the pathogenicity of suspected disease causing variants. In this thesis, I discuss the successful diagnosis of seven individuals in our cohort. Chapters 3-6 describe how four of these molecular diagnoses were achieved and how they contribute to our understanding of disease mechanisms in the respective gene. These chapters specifically discuss SCLT1-related ciliopathies, SPG7 hereditary spastic paraplegia, ALG1 congenital disorder of glycosylation, and SLC39A8 congenital disorder of glycosylation. Chapter 7 outlines the larger results of our study and highlights the key strengths of our approach to using GS and other technologies specifically for providing molecular diagnoses for individuals with a previously identified heterozygous pathogenic variant in an AR disease gene. In Chapter 8, I outline the broader limitations of current approaches to the diagnosis of RDs and how the findings of this thesis have informed our holistic perspective towards using available technologies to improve diagnostic success
Executive Functioning, Stress, and Interpersonal Support in Adults with ADHD
No full textAttention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that affects both children and adults. ADHD symptoms are primarily caused by executive functioning (EF) deficits according to the executive functioning theory of ADHD. Additionally, adults with ADHD are more likely to experience life stress, which is associated with greater challenges with EF. Previous research suggests that interpersonal supports may buffer the negative affects of stress on the executive functioning of adolescents with ADHD symptoms, while the current study extends the investigation to adults with ADHD. A sample of 66 adults with a formal diagnosis of ADHD were recruited for the study. Participants completed the Barkley Deficits in Executive Functioning Scale Short Form (Barkley, 2011), the Holmes and Rahe Stress Scale (Holmes and Rahe, 1967), and the Interpersonal Support Evaluation List (Cohen & Hoberman, 1983). The research questions investigated baseline experiences of EF, stress, and interpersonal support in adults with ADHD, and how EF, stress, and interpersonal support are related based on the stress-buffering hypothesis. Results showed that the majority of adults with ADHD reported experiencing significant EF deficits, at least borderline high experiences of life stress, and moderate levels of interpersonal support. However, no relationship among the variables of interest were noted, and the stress-buffering effect of interpersonal support was not observed. Sample related factors such as education level and gender are discussed as potential explanations for the findings of the study. Additionally, the study discusses potential implications of the findings for adults with ADHD and future research directions
The Karmic Ledger in Four Yuan Zaju Dramatic Texts: Negotiating Family, Debt, and Merchant Ethics of Mongol-Ruled China
No full textQuestions of Seeing, Imagining, and Touching: A Hyper-dialectical Phenomenology of Architectural Drawing After the Digital Image (1960s-1990s)
No full textSince the 1960s, many architects and theorists have proclaimed the death of architectural drawing in the wake of computer-aided design (CAD), yet architectural digital outputs paradoxically remain labeled as architectural drawings, creating a perceptual and epistemological crisis in the discipline. This dissertation examines how digital mediation has altered architects’ perception, which in turn has dialectically reshaped how drawing and design make sense to them. The analysis focuses on two primary mediums, paper and screen, situating itself within Maurice Merleau-Ponty’s phenomenology. Using a hyperdialectical method, this thesis examines how perceptual experiences such as depth, blur, gaze, tactility, zooming, and resolution manifest differently in each medium. The study traces the temporal scope from the 1960s, with the emergence of computer graphics, through the 1970s, when architects became coders, to the 1980s, when computers served as drafting interfaces, and finally to the 1990s, when the so-called digital turn introduced 3D modeling. It contextualizes these developments within a broader trajectory of drawing versus image, referencing earlier visual media such as television, photocollage, and photomontage, framing the computer screen as their inheritor. Focusing on historical texts, user manuals, and artifacts by architects, educators, and theorists, the project critically analyzes how transformative CAD interfaces like Sketchpad, AutoCAD, Photoshop, and Form-Z change the enactive engagement of hand drawing on paper. The research applies the concept of physiognomy, recognizing bodily behavior in response to each experience. For instance, the line, once a record of the hand’s gesture, is now reduced to a cursor’s path, creating a disjunction where the hand no longer draws but moves the cursor, separating vision and touch into distinct, asynchronous acts. This division intensifies a Cartesian split, privileging vision and objectifying space while marginalizing tactile experience. The dissertation concludes that CAD reduces drawing to visual simulations, objective projections, and framed Cartesian images, disconnecting it from its embodied and sensory dimensions. This shift not only changes how drawings are created but also alters their meaning and role in architectural design
Changing cognitive chimera states in human brain networks with age: Variations in cognitive integration & segregation
No full textAging reshapes the brain’s cognitive dynamics by altering the balance between different levels of integration (synchronized activity) and segregation (decreased synchronization). Although the brain’s structural and functional alterations with age are individually well documented, how differences in cognitive abilities emerge from variations in the underlying spatio-temporal patterns of regional brain activity are largely unknown. Dynamic switching between integration and segregation levels across cognitive systems is believed to be crucial for cognitive performance. Using personalized brain network models and cross-sectional data, we analyze age-related variations in dynamical flexibility --- measured through partial synchronization (chimera states) --- across cognitive systems. Our results indicate, among other findings, that the default mode system maintains dynamical flexibility until older age, where overcompensation via heightened variability in chimera states sharply increases, aligning with neural dedifferentiation theory, suggesting reduced specificity. These findings highlight the key role chimera states might play as regulating the integration-segregation balance, offering mechanistic insights into cognitive preservation and decline during aging
Improving ICU Mortality Prediction via Data-Driven Enhancements.
No full textThis study uses administrative health data to examine how important preprocessing techniques affect predictive modeling. In particular, it assesses how model performance is impacted by addressing missing values, class imbalance (for example, through SMOTE), and data sparsity. In addition, the analysis looks at the implications of other data representation formats, such as irregular event sequences, regular time-bin matrices, and event-based sequences, as well as varied temporal window sizes and time bin sizes for fixed windows, window shifts and overlap for sliding windows. The impact of feature selection techniques, such as embedded, filter, and wrapper meth-ods, on predictive accuracy is also evaluated. I used the MIMIC-III electronic health records dataset to illustrate these ideas in practice by comparing the effectiveness of logistic regression, random forest, and multilayer perceptron (MLP) models in predicting mortality. Our findings demonstrate the crucial influence that preprocessing choices, specifically feature selection, windowing, and data representation, have on model performance, and the irregular matrix format consistently demonstrates benefits