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Access status: Open Access ,
The Prevalence of Substance Use in Injured Off-Road Vehicle Drivers: A Systematic Review and Observational Study
(2025-12-15) Rheault, Grace; Not Applicable; Master of Science; Department of Community Health & Epidemiology; Received; NA; Not Applicable; Dr. Jill Hayden; Dr. Mark Asbridge; Dr. David Clarke
Background: Drug driving has become as common as alcohol-impaired driving in Canada and is a major public health issue. Substance use in the context of off-road vehicle driving (i.e., ATVs, snowmobiles, dirt bikes) has not been well-studied in Canada. The prevalence of acute substance use in injured off-road vehicle drivers across Canada is currently unknown. The aim of this study is to estimate the prevalence of acute substance use among injured off-road vehicle drivers in Canada. Objectives: This thesis includes two main studies and three key objectives. Part 1: Systematic Review and meta-analysis The first study involves a systematic review and meta-analysis, with the purpose of (1) estimating the prevalence of acute substance use in drivers involved in off-road vehicle crashes. Part 2: Observational Study The second study is a primary study of injured off-road vehicle drivers presenting to emergency departments across Canada. The two objectives of this study are: (2) to estimate the prevalence of acute substance use in injured off-road vehicle drivers presenting to emergency departments in Canada; and (3) to determine what factors (i.e. demographic, crash characteristics, regional variation) are associated with acute substance use in injured off road vehicle drivers presenting to emergency departments in Canada. Systematic Review Methods: Studies were identified from electronic databases and grey literature. Study selection, data extraction, and risk of bias assessment were completed by two independent reviewers. Descriptive statistics were used to report study characteristics. Random effects meta-analyses were used to report the overall pooled prevalence, and subgroup and sensitivity analyses were used to explore study characteristic effects and the robustness of results. Primary Study Methods: Employing data from the National Drug Driving Study, this study analyzed data from injured drivers presenting to 18 participating EDs across Canada who were in an off-road vehicle crash and had blood drawn for clinical purposes. Excess blood from clinical use underwent toxicology analysis to quantify the presence of impairing substances in the injured driver. Prevalence estimates of substance use in injured off-road vehicle drivers were reported overall, by substance type, by level of alcohol and tetrahydrocannabinol (THC), by number of substances and disaggregated by relevant covariates. Results: 20 publications comprising of 18 studies were included for review, with 2 sets of publications that had overlapping data, drawn from the same studies. Prevalence estimates ranged from 8% to 85%. The overall pooled prevalence estimate of substance use was 41% (95% CI: 28%-54%). There was significant heterogeneity across studies (Q = 3456.38, p < 0.001; I2=99.4%). Subgroup analyses found significant differences between studies using different data sources (coroner’s data: 57% (43%-71%) vs. hospital data (29% (6%-58%), and between non-fatally (29%, 95% CI: 9%-55%) and fatally injured drivers (56%, 95% CI: 43%-69%). The observational study included 473 injured drivers who met the inclusion criteria. Overall, 71% of tested drivers were positive for at least one impairing substance. Alcohol was detected in 38% of drivers, and 69% of those drivers were above the legal blood alcohol concentration (BAC) limit of 0.08% BAC. THC was detected in 17% of drivers. Central nervous system (CNS) depressants were detected in 31%, opioids in 14%, and CNS stimulants in 13% of drivers. About a third (32%) of drivers tested positive for more than one substance. Conclusion: These findings reveal that a large proportion of injured off-road vehicle drivers test positive for substances, which indicates a serious public health issue. Targeted interventions for at-risk populations and increased law enforcement are required to reduce impaired driving among off-road vehicle drivers.
Access status: Open Access ,
UNSOURCED RANDOM ACCESS WITH USER LOCALIZATION AND SENSING
(2025-12-14) Soltani, Roshanak; Yes; Doctor of Philosophy; Department of Electrical & Computer Engineering; Not Applicable; Dr. Ekram Hossain; Yes; Dr. Jason Gu; Dr. Alex Brodsky; Dr. Dmitry Trukhachev
Future wireless networks must support massive numbers of sporadic transmissions while meeting strict spectrum and energy limits. Unsourced random access (URA) provides a grant-free model in which devices transmit without pre-allocated resources and user identifiers and the receiver jointly detects user activity and decodes messages from a large number of users. This thesis advances URA by enabling sensing and localization within the communication process to build scalable frameworks that remain reliable and energy-efficient under heavy loads. It also contributes URA designs that tolerate relaxed synchronization and support longer payloads when needed. Amulti-antenna preamble–payloadURAarchitecture is developed that fuses compressedsensing (CS)-based activity detection with iterative multiuser detection (MUD), decoding, and channel refinement on Rayleigh fading channels. The design is extended to lowscattering regimes through channel models that account for array geometry, consistent with high-frequency environments. Building on this foundation, the thesis applies integrated sensing and communication (ISAC) principles. A location-based URA framework is introduced in which the base station (BS) localizes active users while detecting and decoding their data using only uplink signals. The method ties user transmission features to angle-ofarrival (AoA) and partitions space into sectors with sub-pool allocation and reuse to reduce collisions and complexity. Localization improves communication by providing spatial information that helps separate multiple packets. The concept is further generalized in the random-access procedure. The thesis also demonstrates environment sensing where user uplink signals act as opportunistic illuminators for multi-object sensing at the BS, revealing the synergy and trade-offs between sensing and communication. Some structural challenges of URA are also addressed. Scalability under timing uncertainty is achieved through a fully asynchronous URA design that removes slot and beacon requirements and performs sliding window timing acquisition together with MUD on the Gaussian channel. For longer messages a multi-segment URA structure is proposed that stitches decoded segments across consecutive slots and employs a dual preamble pool to identify the first segment and reduce collisions. Together, these studies show how URA can jointly deliver reliable data detection, user localization, and environmental sensing with high scalability, paving the way for intelligent and spectrum efficient random-access in future networks.
Access status: Embargo ,
A TRIPLE-MODALITY STRATEGY OF NKT CELL IMMUNOTHERAPY, ONCOLYTIC VIROTHERAPY, AND CHECKPOINT BLOCKADE FOR LUNG CANCER
(2025-12-15) Lukacs, Jordan; Not Applicable; Doctor of Philosophy; Department of Microbiology & Immunology; Not Applicable; Dr. Mansour Haeryfar; Not Applicable; Dr. Jeanette Boudreau; Dr. Graham Dellaire; Dr. Roy Duncan; Dr. Brent Johnston
Lung cancer is the leading cause of cancer-related deaths in Canada. Current standard therapies, such as chemotherapy, radiation therapy, or immune checkpoint blockade (ICB) are often ineffective on their own due to severe adverse effects and acquired drug resistance. Therefore, new treatments that are safer and more effective are needed. Recent clinical trials combining ICB with other therapies have demonstrated durable outcomes in some patients with lung cancer. Here I examined the efficacy of combining PD-1 checkpoint blockade with natural killer T (NKT) cell activation therapy and recombinant oncolytic vesicular stomatitis virus (VSV-ΔM51) expressing cytokines IL-12 (VSV-IL-12) or IL-15 (VSV-IL-15), or fusion- associated small transmembrane (FAST) proteins p14 (VSV-p14), p15 (VSV-p15), and p14endp15 (VSV-p14endp15). VSV-p14, VSV-p15, and VSV-p14endp15 demonstrated enhanced immunogenic cell death and killing capacity relative to the parental virus (VSV-GFP) in lung cancer cells, in vitro. Furthermore, VSV-FAST constructs induced PANoptosis and overcame the blockade of multiple programmed cell death pathways to effectively eliminate lung cancer cells. In a genetic mouse model of lung adenocarcinoma, the combination of VSV-p14, VSV-p15, or VSV-p14endp15 with NKT immunotherapy increased overall survival relative to untreated mice. Addition of PD-1 blockade to NKT immunotherapy and VSV-FAST constructs significantly extended the survival over untreated mice. Mixed delivery of VSV-p15 and VSV- IL-12, along with NKT immunotherapy and PD-1 inhibition, had the greatest increase in overall survival of all tested combinations. Maintenance therapy with multiple rounds of VSV-p15/NKT activation/PD-1 blockade also led to significantly enhanced overall survival rates in this model, however some female mice experienced adverse reactions to the treatment. Despite increases in overall survival and increased numbers of NKT cells in the lung and spleen, there were no significant differences in total tumor area or total number of other immune cell populations within the lungs of treated mice compared to untreated mice. We also observed increased VSV neutralizing activity in the serum of treated mice, suggesting potential challenges with repeated systemic VSV treatments. Collectively, our findings demonstrate that the combination of PD-1 blockade with NKT cell immunotherapy and oncolytic VSV-p15/VSV-IL-12 presents a promising strategy for the treatment of lung cancer.
Access status: Open Access ,
Spatial and Temporal Mechanisms Controlling Convection Over The Great Plains
(2025-12-15) Verevkin, Iaroslav; Not Applicable; Doctor of Philosophy; Department of Physics & Atmospheric Science; Not Applicable; Yanping Li; Yes; Thomas Duck; Glen Lesins; Ian Folkins
The central United States exhibits an anomalous summertime diurnal cycle of precipitation, characterized by an afternoon maximum over the Rocky Mountains that transitions to a nocturnal maximum over the Great Plains. This phenomenon, which remains a challenge for many numerical models, is governed by the interaction of processes spanning multiple scales. This thesis investigates the spatial, temporal, and dynamical mechanisms controlling this diurnal cycle through a comprehensive, climatologically-grounded multi-year analysis of satellite-derived precipitation data Integrated Multi-satellitE Retrievals for GPM (IMERG) and hourly meteorological analyses Rapid Refresh and Rapid Update Cycle (RAP/RUC). The research is presented in three parts. First, the spatial variation in the synoptic structure of convective systems is examined. The analysis reveals a distinct transition in dominant forcing mechanisms with distance from the mountains: convection in the “Near Plains” (west of 100◦W) is significantly influenced by mountain-initiated solenoidal circulations, while convection in the “Far Plains” is more closely associated with the dynamics of the Great Plains Low-Level Jet (GPLLJ). Second, the thesis investigates the diurnal evolution of vertical profiles of convection. A systematic diurnal shift from surface-based to elevated convection is identified, which consistently occurs as the nocturnal boundary layer stabilizes. This shift is linked to a threshold in the low-level lapse rate of approximately -4 to -5 K/km, providing a quantifiable metric for the influence of boundary layer thermodynamics on the convective mode. Finally, the thesis examines the climatological eastward propagation of rainfall. The analysis demonstrates that the diurnal, clockwise rotation of the GPLLJ’s wind vector drives a propagating pattern of low-level mass convergence across the plains. This mechanism is modulated by topographically-induced suppression of afternoon convection via enhanced convective inhibition (CIN), enabling the nocturnal, dynamicallydriven rainfall maximum to dominate.
Access status: Open Access ,
UTILIZING MACHINE LEARNING TO DETECT TOR TRAFFIC: A REALISTIC DATASET AND A PRELIMINARY ANALYSIS
(2025-12-15) Sadik, Md Rafiqul Islam; Not Applicable; Master of Computer Science; Faculty of Computer Science; Not Applicable; Dr. Xichen Zhang; Not Applicable; Dr. Samer Lahoud; Dr. Qiang Ye
With the increasing use of anonymization technologies such as the Tor network, the ability to accurately differentiate Tor traffic from conventional Internet traffic has become an important challenge for network analysis and security monitoring.This thesis presents a fully controlled and reproducible framework for generating realistic Tor and Non-Tor traffic datasets to support the evaluation of encrypted traffic detection techniques. The framework integrates a Debian workstation, a Whonix gateway for Tor routing, and a noise-free AWS-based web server, combined with Selenium-driven automation to execute identical user activities over both Tor-based and Non-Tor-based network paths.Using this environment, a comprehensive dataset was generated across six application categories: web browsing, video streaming, file transfer, instant messaging, voice over IP, and video conferencing. A set of six machine-learning models-Decision Tree, Random Forest, XGBoost, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN) was evaluated on the generated dataset. Experimental results demonstrate that traditional treebased models, particularly Random Forest and XGBoost, consistently outperform deep-learning approaches, achieving high detection accuracy in distinguishing Tor from Non-Tor network flows across all traffic types.These findings highlight both the effectiveness of classical machinelearning approaches and the importance of realistic dataset generation in advancing encrypted traffic classification research.
Access status: Open Access ,
Continuous Ceilometer-Derived Mixed Layer Height Observations at an Eddy Covariance Flux Tower Site in the Semi-Arid U.S. Southwest
(2025-12-15) Mengering, Deklan; No; Master of Science; Department of Physics & Atmospheric Science; Not Applicable; n/a; Not Applicable; Rachel Chang; Daniel Nadeau; Manuel Helbig
The planetary boundary layer (PBL) is the atmospheric layer directly influenced by the Earth’s surface. The height of the top of the PBL (PBLH) is a key parameter that determines the extent of vertical mixing, which plays a crucial role in micrometeorology, pollution dispersion, and the exchange of energy and matter between the land and the atmosphere. In the past, PBLH estimates have relied largely on observations with low temporal resolution (radiosondes) or on modelling outputs (reanalysis). However, growing interest in the integration of PBLH measurements at surface energy flux tower sites has highlighted the temporal, spatial, and financial trade-offs that come with different PBL height measurement techniques. Of the available techniques, ceilometers offer a promising solution, as they have the potential for wide-range integration at a comparatively low cost. However, there is no publicly available, cross-platform algorithm for the detection of the PBL using ceilometer data. In this study, we developed a Python-based algorithm that can be applied to Lidar backscatter profiles from different ceilometer types. We use this algorithm to create a 5-year time series of PBLH estimates from a semi-arid high desert ecosystem in Arizona. The ceilometer PBLH estimates were compared to PBLH estimates using three independent approaches: reanalysis data, nearby National Weather Service radiosonde observations, and on-site field radiosonde campaigns. We use these estimates to validate the PBL heights derived using the newly developed algorithm. The time series of PBLH measurements is then used in combination with surface energy flux observations to investigate the relationship between PBL growth dynamics and the surface energy balance measured at a nearby flux tower. The maximum daily mean PBLH occurred in June, reaching 3100 m when the median Bowen ratio for the month was 2.6. The PBLH then decreased by 200 m in July, and another 300 m in August when the Bowen ratios dropped to 0.7 and 0.2, respectively. The results show that strong land-atmosphere coupling is characteristic for the site, with both the terrestrial (i.e. soil moisture to surface flux) and the atmospheric (i.e., surface flux to boundary layer atmosphere) legs playing an important role for the seasonal dynamics of PBLH. This study demonstrates how ceilometer-derived PBLH estimates at surface energy flux tower sites can be used to improve the current understanding of land-atmosphere coupling.