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Characterization of Online Graphene Oxide and Reduced Graphene Oxide using optical diagnostics
No full textGraphene is a promising nanomaterial due to its high electron mobility, large specific surface area, high thermal conductivity, high tensile strength, and flexibility. In electrical applications, pristine single-layer graphene (PG) offers superior properties compared to conventional materials in semiconductors, supercapacitors, and batteries. However, since PG is difficult to manufacture at an industrial scale, there is a need for a graphene-like material that is amenable to high-yield production. A promising candidate is the thermal reduction of graphene oxide (GO) into reduced graphene oxide (rGO), which allows for high throughput of material while minimizing human intervention. However, the properties of rGO are heavily
dependent on the quality of incoming GO and the resulting morphology and composition of the rGO. Therefore, a method to measure the GO and rGO properties in real time is needed. Time-resolved laser-induced incandescence (TiRe-LII) and line-of-sight attenuation (LOSA) are two absorption-based measurements that are commonly used to characterize soot and other nanomaterials in real time. Consequently, these methods are thought to have high potential in characterizing GO and rGO.
In this work, ex situ methods were used to provide morphological and optical characteristics of GO. Additionally, TiRe-LII and LOSA testing were performed to assess their capabilities in measuring GO and rGO in real-time. The results show that TiRe-LII is capable of providing the relative specific surface area (SSA) of rGO, with accurate SSA trends and slight deviations in absolute value compared to ex situ testing. However, GO showed no incandescent signals due to its low absorption characteristics.LOSA testing showed that, by applying the Lorentz-Drude model, the electrical conductivity and degree of reduction of GO and rGO could be derived. The results indicated that the derived electrical conductivity matched expected trends and were similar in magnitude to literature results. This study found that TiRe-LII can be used to derive the SSA of rGO, and LOSA can be used to derive the electrical conductivity of GO and rGO, both in real time
Using a Capability Sensitive Design Approach to Support Newcomers Well-being
No full textNewcomers transitioning to a new country face many challenges, and their well-being is impacted due to unfamiliarity with self-navigating in a new environment. This thesis explores how Capability Sensitive Design (CSD) can be operationalized to guide the end-to-end design and evaluation of technologies that support the well-being of newcomers during life transitions. While the CSD framework has recently been investigated in Human Computer Interaction (HCI) for its ethical focus on supporting what individuals have reason to value, there remains a gap in how it can be translated into concrete, scalable technology design processes. To address this, we present a multi-stage methodology that includes formative
interviews, co-design sessions, prototype development, and a longitudinal field study to evaluate the application prototype. We begin by mapping the lived experiences of newcomers using a capability-oriented interview protocol and with the use of a capability board to surface valued goals and challenges. This informed a co-design process using modified capability cards, where both newcomers and organizational stakeholders ideated design features aligned with the ten central capabilities. Drawing on these insights, we developed the Newcomer App—a multilingual mobile platform offering four core features: goal-oriented planning, capability-aligned suggestions, resource search and browsing, and reflective tracking. We evaluated this platform in an eight-week field study that included in-app activity logging and post study interviews. Our findings show that newcomers were able to identify capability-aligned goals which they found helpful, translate them into intentional plans, and reflect on both their achievements and the conversion factors that influenced outcomes. Importantly, we observed how CSD-informed features constructed self-discovery, increased agency, and facilitated social contribution, particularly in the capabilities of social connection, emotional well-being, and community participation. The study also highlighted the importance of contextual and social barriers in determining whether users could turn suggestions into meaningful actions. This thesis contributes an operational model for applying CSD across the full design lifecycle, offering insights for researchers and practitioners. By translating ethical commitments into deployable technologies, our work extends prior research in HCI and design social justice, demonstrating how technologies can support equitable pathways toward wellbeing for marginalized groups, such as newcomers in navigating complex transitions
Electrochemical Capacitance-Voltage Profiling of Carrier Distributions in Advanced III-V Semiconductor Epitaxial Structures
No full textThis thesis presents a comprehensive investigation of electrochemical capacitance-voltage (ECV) profiling for the characterization of carrier concentration profiles in III-V semiconductor heterostructures, with a focus on GaAs, InAlAs, and GaN. The methodology of ECV is demonstrated in detail, including electrolyte preparation, surface etching mechanics, and data interpretation. ECV profiling of staircase structures is used to calibrate doping concentrations during epitaxial growth, enabling precise evaluation of growth parameters. In low-temperature grown (LTG) GaAs, undoped layers exhibit n-type behavior attributed to excess As antisites, consistent with prior deep-level defect studies. Parabolic Quantum Well (PQW) and Si-δ-doped structures are analyzed, with carrier profiles compared directly against nextnano simulations to address total available carriers and doping accuracy. Electrolyte comparisons show that 0.2M NaOH/0.1M EDTA/10% vol. ED yields superior etch uniformity, while 0.1M Tiron offers sharper resolution with trade-offs in etched surface quality. The study confirms ECV as a valuable diagnostic and calibration tool for advanced semiconductor device development and doping control
Reinforcement Learning Based Motion Planner and Trajectory Tracker for Unmanned Aerial Systems
No full textUnmanned aerial vehicles (UAVs) are increasingly used for autonomous tasks such as inspection, maintenance, and search-and-rescue. However, effective trajectory tracking and obstacle avoidance in dynamic environments remain challenging. Traditional optimization-based methods lack adaptability and computational efficiency, motivating the use of reinforcement learning (RL) for UAV control. This thesis explores RL-based UAV trajectory tracking through three key phases: benchmarking RL algorithms, developing a dual-agent RL framework, and leveraging these insights to design a model-free RL approach for aerial continuum manipulators (ACMs).
First, off-policy RL algorithms including DDPG, TD3, SAC, and SoftQ, are benchmarked to evaluate their generalization from simulation to real-world UAV path planning. Results showed DDPG excelling in reward maximization while TD3 provided superior collision avoidance. These insights guided the development of a dual-agent RL framework for UAV trajectory tracking in cluttered environments. The system used two RL agents: one for velocity prediction and another for real-time collision avoidance, leveraging 3D point cloud data to eliminate memory-intensive obstacle representations. Simulated and real-world experiments demonstrated improved trajectory tracking, obstacle avoidance, and adaptability over single-agent and optimization-based approaches.
Building on this, a model-free RL framework for ACMs is introduced, which integrate UAV mobility with continuum robotic arms for dexterous aerial manipulation. Traditional RL struggles with constraint enforcement, leading to unsafe behaviors. To address this, a health-driven RL architecture is proposed that implicitly incorporates constraints through a secondary health reward, ensuring safe and stable operation. Using 3D point cloud data for navigation and a curriculum learning paradigm for scalability, the framework demonstrated superior performance over state-of-the-art RL and optimization techniques in trajectory tracking and constraint adherence.
This thesis advances RL-based aerial control through benchmarking, dual-agent learning, and safe RL integration for complex aerial systems. The findings lay the groundwork for future research in refining metrics, exploring additional algorithms, and incorporating vision-based RL for enhanced perception and decision-making
Expanding the bat toolbox: Carollia perspicillata bat cell lines and reagents enable the characterization of viral susceptibility and innate immune responses
No full text© 2025 Gonzalez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Multiple viruses that are highly pathogenic in humans are known to have evolved in bats. How bats tolerate infection with these viruses, however, is poorly understood. As viruses engage in a wide range of interactions with their hosts, it is essential to study bat viruses in a system that resembles their natural environment like bat-derived in vitro cellular models. However, stable and accessible bat cell lines are not widely available for the broader scientific community. Here, we generated in vitro reagents for the Seba's short-tailed bat (Carollia perspicillata), tested multiple methods of immortalization, and characterized their susceptibility to virus infection and response to immune stimulation. Using pseudotyped virus library and authentic virus infections, we show that these C. perspicillata cell lines derived from a diverse array of tissues are susceptible to viruses bearing the glycoprotein of numerous orthohantaviruses, including Andes and Hantaan virus and are also susceptible to live hantavirus infection. Furthermore, stimulation with synthetic double-stranded RNA prior to infection with vesicular stomatitis virus and Middle Eastern respiratory syndrome coronavirus induced a protective antiviral response, demonstrating the suitability of our cell lines to study the bat antiviral immune response. Taken together, the approaches outlined here will inform future efforts to develop in vitro tools for virology from non-model organisms and these C. perspicillata cell lines will enable studies on virus-host interactions in these bats.National Institute of Allergy and Infection Diseases of the National Institutes of Health (NIAID/NIH), 1R21AI169527 || NIAID/NIH, R 21AI156482 || NIAID/NIH, P20GM134974 || Natural Sciences and Engineering Research Council of Canada (NSERC), RGPIN-2022-03010 || NSF Biology Integration Institute, NSF DBI 2021909 || NSF Biology Integration Institute, NSF DBI 2213854 || NSERC, #569587-2022 || Government of Saskatchewan, Innovation Saskatchewan and the Ministry of Agriculture || Canada Foundation for Innovation, Major Science Initiatives Fund
Beyond the screen: Exploring the dynamics of social media influencers, digital food marketing, and gendered influences on adolescent diets
No full text© 2025 Amson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Adolescent obesity remains a public health concern, exacerbated by unhealthy food marketing, particularly on digital platforms. Social media influencers are increasingly utilized in digital marketing, yet their impact remains understudied. This research explores the frequency of posts containing food products/brands, the most promoted food categories, the healthfulness of featured products, and the types of marketing techniques used by social media influencers popular with male and female adolescents. By analyzing these factors, the study aims to provide a deeper understanding of how social media influencer marketing might contribute to dietary choices and health outcomes among adolescents, from a gender perspective, shedding light on an important yet underexplored aspect of food marketing. A content analysis was conducted on posts made between June 1, 2021, and May 31, 2022, that were posted by the top three social media influencers popular with males and female adolescents (13-17) on Instagram, TikTok, and YouTube (N=1373). Descriptive statistics were used to calculate frequencies for posts containing food products/brands, promoted food categories, product healthfulness, and marketing techniques. Health Canada's Nutrient Profile Model was used to classify products as either healthy or less healthy based on their content in sugar, sodium, and saturated fats. Influencers popular with males featured 1 food product/brand for every 2.5 posts, compared to 1 for every 6.1 posts for influencers popular with females. Water (27% of posts) was the primary food category for influencers popular with females, while restaurants (24% of posts) dominated for males. Influencers popular with males more commonly posted less healthy food products (89% vs 54%). Marketing techniques varied: influencers popular with females used songs or music (53% vs 26%), other influencers (26% vs 11%), appeals to fun or coolness (26% vs 13%), viral marketing (29% vs 19%), and appeals to beauty (11% vs 0%) more commonly. Influencers popular with males more commonly used calls-to-action (27% vs 6%) and price promotions (8% vs 1%). Social media influencers play a role in shaping adolescents' dietary preferences and behaviors. Understanding gender-specific dynamics is essential for developing targeted interventions, policies, and educational initiatives aimed at promoting healthier food choices among adolescents. Policy efforts should focus on regulating unhealthy food marketing, addressing gender-specific targeting, and fostering a healthy social media environment for adolescents to support healthier dietary patterns.International Food Policy Study Youth Survey, Health Canada || Canadian Institutes of Health Research (CIHR) Project Grant, PJT-162167 || Fonds de recherche du Quebec - Sante, 2022-24 || Canada Research Chairs program
Development and application of aquatic ecosystem monitoring approaches for the Peace-Athabasca Delta and Whooping Crane Nesting Region of Wood Buffalo National Park
No full textShallow waterbodies are abundant in northern regions where their small water volume and large surface area-to-volume ratio make them vulnerable to effects of climate change, natural resource development and long-distance transport of contaminants. Canada’s largest national park, Wood Buffalo National Park, spans the NWT-Alberta border and contains two Ramsar Wetlands of International Importance: The Peace-Athabasca Delta (PAD) and the Whooping Crane Nesting Region (WCNR; hereafter referred to as the Whooping Crane Summer Range (WCSR)). These aquatic landscapes play vital roles in supporting biodiversity and traditional livelihoods of Indigenous Peoples of the region, and in providing habitat for the threatened wood bison (Bison bison athabascae) and the endangered whooping crane (Grus americana). They also underpin the park’s designation as an UNESCO World Heritage Site. Despite these recognitions, increasing concern over aquatic ecosystem degradation due to climate change and industrial development prompted UNESCO to evaluate the park’s status in 2017 and whether it should be downgraded to ‘World Heritage in Danger’. In response, Parks Canada developed an Action Plan in 2019, which was supported by federal investment of $87 million towards its implementation. Key actions include the development and implementation of an integrated aquatic ecosystem monitoring program for the PAD and WCSR to assess how aquatic ecosystems in these landscapes respond to multiple potential stressors – a need that has long been recognized.
Monitoring aquatic ecosystems in remote, hydrologically diverse landscapes poses significant challenges, particularly in balancing the need for comprehensive spatial and temporal data with logistical and financial constraints. Effective sampling methodologies that can track changes across a range of timescales (e.g., from hours to years) at a landscape scale can help overcome these barriers and generate critical knowledge to support aquatic ecosystem monitoring programs. At the PAD and WCSR, hydrological processes strongly influence the physical, chemical, and biological conditions of waterbodies. Thus, tracking these processes across space and time must serve as the cornerstone of an aquatic ecosystem monitoring program designed to address longstanding concerns about reduced freshwater availability due to hydroelectric regulation of the Peace River by the WAC Bennett Dam and potential contamination from upstream Alberta Oil Sands operations.
This thesis reports results obtained during 2015-2022 using integrated, multi-faceted field-sampling approaches to investigate the responses of shallow waterbodies in two ecologically significant landscapes to anthropogenic stressors. Given the foundational role of hydrology in shaping these aquatic ecosystems, a multi-method approach was used to characterize influential hydrological processes, including episodic river flooding at the PAD, groundwater discharge in the WCSR, as well as precipitation and evaporation. The sampling spanned from continuous hourly water depth measurements to systematic seasonal (spring, summer, fall) measurement of water isotope tracers and water chemistry surveys at ≥60 waterbodies across both landscapes over multiple consecutive years. Additional approaches were employed to assess enrichment of nickel and vanadium, key oil sands indicators, at lakes across the PAD.
Key findings presented in this thesis are organized across three data chapters, each contributing advancements to understanding the hydrological processes shaping shallow waterbodies in the PAD and WCSR, as well as contaminant enrichment in fluvial-derived sediment to lakes in the PAD. In Chapter 2 continuous water depth measurements were used to develop a new lake classification scheme for the PAD based on four distinct depth variation patterns associated with a singular, dominant hydrological process: 1) ‘Drawdown’ (≥15 cm decline) by evaporation and/or outflow after ice-jam floods, 2) ‘Stable’ lake levels (<15 cm change) sustained by rainfall, 3) ‘Gradual Rise’ by inundation from the open-drainage network, and 4) ‘Rapid Rise’ by input of river floodwater. River flooding during the open-water season has not been well recognized as an important recharge mechanism for lakes in the PAD, yet it occurred extensively in the Athabasca sector in 2018 and 2019. Retrospective analysis of past peak summer levels of the Athabasca River revealed that open-water flooding equivalent to that of 2018 has likely occurred during 16 years since 1982 (42% of the years). Thus, open-water flooding, a phenomenon rarely reported on in the scientific literature, is a common hydrological process affecting broad areas of the Athabasca sector of the delta. Chapter 3 synthesizes evidence gathered during a 7-year research program at the PAD (from which Chapter 2 emerged) to explore the associations between lake ecosystem processes in the PAD and climate indices, assess if upstream industrial activities have enriched concentrations of substances of concern, and provide a foundation for multi-faceted aquatic ecosystem monitoring at the PAD. Integration of evidence from key metrics, including isotope-inferred lake water balance, water chemistry and contaminant enrichment, was used to identify status and trends over space and time and assist with identifying causes of change. The research coincided with a period of marked climatic variation, which provided opportunity to evaluate the effectiveness of the methodologies and responses of lakes to changes in hydrology and climate. Four key recommendations are provided to operationalize the methodologies and approaches presented in Chapter 3, which strive to maximize the information content of cost-effective measurements to sustain a long-term monitoring program. Chapter 4 extends use of the methodologies beyond the PAD to 63 shallow ponds in the WCSR, to characterize key hydrological processes and their spatial and seasonal patterns in 2022. Peak water levels occurred in spring when consistently low isotope compositions and low concentrations of major nutrients and ions reveal widespread, profound influence of snowmelt runoff. Spatial variability of these measurements increased during summer and fall as connectivity to groundwater waned and influence of evaporation increased at some waterbodies. Water level drawdown was less at waterbodies with strong versus weak groundwater connectivity (median = 23% vs 44% of initial depth, respectively). Geospatial interpolation of a multi-metric ‘Vulnerability Index’, based on isotope-inferred evaporation-to-inflow ratios, water-level drawdown and water chemistry ordination sample scores, identified that Whooping Crane nest locations in 2022 cluster within areas where waterbodies retained strong connectivity to groundwater.
Collectively, this research aims to inform the design and implementation of sustainable, long-term monitoring programs for shallow aquatic ecosystems in the PAD and WCSR to enable rapid detection of changes and their causes in the face of accelerating industrial development and climate change. The knowledge gained can be used to guide policy decisions under the WBNP Action Plan, and the methodologies may be applied at other remote, water-rich landscapes to evaluate for changes caused by multiple potential stressors
Order Fulfillment Optimization in Automated Warehouses
No full textIn warehousing, order batching is one of the most popular strategies for optimizing order fulfillment as it groups similar orders into the same batch to optimize picking. The order similarity can be determined based on item locations, availability, and order compositions. The objectives include minimizing travel time, maximizing the number of picked items, and maximizing simultaneous multi-order processing. In this thesis, we study the order fulfillment problem in automated warehouses and propose an order fulfillment heuristic method that to minimize the number of required pick-up sequences to fulfill given order lists by integrating various independent order fulfillment techniques. Three independent algorithms are modified and integrated: (1) FP-Growth-based Association Rule Mining, (2) Order Batching using Similarities Between Orders, and 3) A Hybrid of Public and Personal Item Storage. The resulting heuristic approach is capable of finding optimal solutions when compared to exact results based on Integer Programming. Additionally, a custom-built Python simulation platform is created and run to prove the scalability of the devised algorithm. The Python simulation platform has been further developed into an ROS- and Gazebo-communicable simulation platform for more visualized and intuitive simulation results. Based on the simulation results involving 2000 orders and 1000 items, the algorithm reduced the total number of required pick-up sequences by approximately 50% in comparison to traditional First-Come, First-Served approach
Edge-Coloring Planar Graphs and the Cycling Conjecture
No full textAn r-graph is defined to be a graph where each vertex has degree r and any odd subset has at least r edges leaving it. This thesis focuses on the conjecture that any planar r-graph can be edge-colored with r colors. Past work has shown that the conjecture holds for r ≤ 8, but it becomes more difficult with each increase of r. We consider what occurs when r is very large. The main ideas of the thesis work with a minimal counterexample graph that is one of the smallest graphs to contradict the conjecture for a given r. To make a minimal counterexample easier to work with, we generalize to grafts, working with T-joins and T-cuts. We go through various directions to approach the problem and show properties of a minimal counterexample as well as questions that stand in the way of proving it does not exist
Trait preferences and lentil varietal adoption in central Ethiopia: A multistakeholder approach
No full text© 2025 Najjar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Agricultural technologies, including modern/improved crop varieties, are a critical measure for improving productivity, meeting food security needs, and bridging inequalities. This notwithstanding, adoption of some improved crop varieties in sub-Saharan Africa (SSA) tends to be low, with factors such as limited information, poor access to inputs, and risk averseness cited as reasons for low adoption. Few studies in SSA, and Ethiopia particularly, examine the influence of lentil trait preferences on adoption, and the ones that do only look at farmers' perspectives who are often treated as a homogenous group. This is despite the importance of lentils as a subsistence and growing market crop, and the fact that diverse factors may determine adoption among farmers. To address these knowledge gaps, this study used a mixed methods approach involving multiple stakeholders (n=808) to understand gendered patterns in lentil varietal adoption and trait preferences, using an intersectional lens. The findings revealed low adoption rates for improved varieties for women and men alike due to poor disease resistance, and insufficient attention from the breeding programs to preferred processing and consumer traits, a well as the differentiated needs of farmers. Paying attention to these trait needs serves to inform gender-intentional breeding and improve the income generation potential of lentil varieties for diverse farmer groups. As such, we recommend sex-disaggregated data collection from socially differentiated groups and market representatives in order to inform breeding priorities along with the development of multiple varieties that suit different needs.CGIAR Initiative on Market Intelligence and Produce Profile Initiative (MIPPI) || CGIAR Gender Platform (through Bill and Melinda Gates Foundation)