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Investigating the use of paper mill residuals as agricultural soil amendments in Thunder Bay, Ontario
Full text linkThis study investigates the repurposing of pulp and paper mill residuals as soil amendments for agriculture around Thunder Bay, Ontario, Canada. Two pulp and paper mill residuals, wood ash (WA) and pulp and paper mill mixed biosolids (PPMS), were applied to agricultural soils as a liming agent and organic amendment, respectively, to improve soils and plant productivity. To determine the suitability of soils in the area to receive these materials under Ontario’s Nutrient Management Act and O.Reg. 267/03, soils from 17 farms in the Thunder Bay area were collected and analyzed to establish heavy metal and fertility ranges. Soils were then collected from three farms in the area for a greenhouse pot experiment. The pot experiment was designed to compare the effects of adding PPMS and WA separately and in combination with and without the addition of supplementary mineral fertilizers in accordance to O.Reg 267/03, the legislation regulating the land application of these materials in Ontario. The addition of PPMS at recommended rates significantly increased grass yield, soil organic matter (SOM) concentrations, nutrient availability, pH, and soil health scores, demonstrating the benefits that land application of PPMS can offer to area growers. In soils that require a pH adjustment and could benefit from additional organic matter, the results showed applying WA and PPMS together is more beneficial when either are applied alone. Results indicate that the application of WA and PPMS in the ratio of 1:3 (by mass) had the greatest benefit. The benefits observed were immediate but may not be realized in the year of application in the field due to weather constraints that may constrain the solubility of inorganics and the decomposition and solubility of organic materials
Shaping my Latinx body in Canada: challenging internalized anti-fat bias
Full text linkThis research project explores my journey as a Mestizo Latinx Immigrant woman in
Canada and how, with a body transformation, I came to realize that I have an internalized anti-fat
bias. As an autoethnographer, I delve into my life experiences, feelings, and memories to
discover when this started and how much family, cultural context, education, and healthcare
systems influenced its development. In this thesis, I discuss themes such as intersectional
oppression, immigration, colonization, family interactions, and anti-fat stigma and bias, mostly in
my home country, but also what I have experienced in two years of living in Canada. The
findings of this research show: how the lack of attention on topics such as body and food
relationships in the educational system affects the later development of a distorted body image
and possible eating problems; how the colonization system influenced centuries of history such
that a family can be led to grow with anti-fat stigma and bias; and how many racist ideals are
perpetuated and enforced in younger generations, which in my case meant being forced into
restricted dieting all my life. Finally, through the literature and analysis, this thesis examines and
deconstructs how I reached the point where “fat” became a liberating word, a word of power,
rather than a negative descriptor used to make me feel inferior. Through research, I built a new,
powerful definition that empowers my body image, heals my journey, and leads me to advocate
for a more diverse and inclusive world with different body shapes and sizes
The radial wrist as a morphological and functional unit in extant African apes and humans
Full text linkPrevious research has identified multiple aspects of carpal (i.e., wrist bones) morphology
in Homo sapiens (humans) and some fossil hominin species that may reflect adaptations to the
habitual use and manufacture of stone tools, particularly among bones from the radial side of the
wrist (i.e., the, trapezium, trapezoid, scaphoid, and capitate). Using three-dimensional (3D)
surface models of radial-side carpals and 3D geometric morphometrics (3DGM), this study aims
to quantify the shape variation of this anatomical region among extant African apes and humans.
Extending on previous studies that have typically quantified carpal morphology by studying each
bone individually and in isolation from each other, this study marks the first time where these
four radial-side carpals are quantitatively analyzed together as articulated units. Based on
previous descriptions as well as qualitative and quantitative analyses, Pan troglodytes
(chimpanzees), Pan paniscus (bonobos), and Gorilla gorilla gorilla (western lowland gorillas)
wrists were predicted to display features that facilitate radioulnar stability and
proximodistally-directed loading, which would be more efficient for locomotor behaviours.
Conversely, human wrists were predicted to display features that facilitate proximodistal stability
and radioulnarly-directed loading, which would be more efficient for manual dextrous
behaviours. Results showed that the combined shapes of these carpal bones, as well as their sizes
and orientations relative to each other, vary considerably between the African ape and human
samples. The African ape wrists showed, as predicted, a complex of features that provides
biomechanical advantages for withstanding and distributing forces directed proximodistally
during knuckle walking and other locomotor behaviours. In contrast, the human wrists displayed
a complex of features that appears to provide biomechanical advantages for withstanding and
distributing large forces directed radioulnarly during human-like power and precision grips
Estimating high-pressure hydrogen storage required to refuel heavy-duty vehicles
No full textOne of the major challenges of the current generation, in Canada, is meeting the ambitious net-zero emission targets by 2050 to fend off the worst impacts of climate change. Heavy-duty (HD) hydrogen fuel cell electric vehicles (FCEV) present an opportunity to drastically cut greenhouse gas emissions produced in the transportation sector. A major hurdle in HD FCEV deployment is the design, development and implementation of hydrogen refueling stations (HRS), specifically estimating the high-pressure hydrogen storage required to refuel HD FCEVs. In this research, a numerical model was developed to estimate the high-pressure hydrogen storage required to refuel HD FCEVs with an on-board storage of 80 kg at a nominal working pressure (NWP) of 70 MPa achieving 100% state of charge (SOC). Equations of State (EoS) and Generalized Reduced Gradient (GRG) nonlinear programming are used throughout the numerical model to estimate the hydrogen storage pressure and the change of internal energy of various cascading strategies. The numerical model is validated against experimental testing performed at a specialized hydrogen test lab in Surrey, British Columbia. A parametric study focusing on the effect of storage and vehicle temperature on the numerical model is conducted. The numerical model is used to investigate the effects of increasing the storage pressure, storage volume and the number of cascades, based on energy consumption and volume ratio. Finally, a case study for refueling a 1,500L FCEV is performed, considering the available hydrogen storage at a hydrogen test facility located in Surrey, BC. A cascading strategy for HD fueling is suggested based on overall energy consumption
Experimental and numerical investigation of drug delivery and aerosol deposition in the mouth-throat airway using a pressurized metered dose inhaler (pMDI)
No full textInhalation therapy is a widely used and effective method for treating respiratory diseases such
as asthma and chronic obstructive pulmonary disease (COPD). Among the various inhalation
devices, pressurized metered-dose inhalers (pMDIs) are the most commonly utilized due to their
portability and rapid onset of action. However, despite their popularity, challenges remain in
ensuring efficient and targeted drug delivery to the lungs. Factors such as airflow dynamics,
inhalation profiles, device actuation, and anatomical variations can significantly impact drug
deposition, particularly in the mouth-throat (MT) region, where substantial particle loss is often
observed.
This study aimed to improve the performance of inhalation therapy devices by leveraging insights
gained from experimental in vitro studies and computational fluid dynamics (CFD) simulations.
The thesis combines experimental measurements with CFD simulations (including USP-IP,
COPD, and CF inhalation, pediatric geometry, and mucus modeling) to investigate the transport
and deposition behavior of pharmaceutical aerosols delivered by pMDI devices.
The experimental studies utilized an eight-stage Next Generation Impactor (NGI) setup paired with
an industrial induction port (IP) and three-dimensional (3D)-printed mouth-throat geometries to
quantify the deposition fraction on each stage, allowing for the plotting of particle size distribution.
To facilitate this research, the geometry of the mouth-throat region was constructed using 3D
printing technology with Ultimaker S3 and S5 printers, employing tough polylactic acid (PLA) for
precise and durable models. High-performance liquid chromatography (HPLC) was used at the
inhaler, MT geometry, and collection cup of each stage of the NGI to accurately measure the
deposition of the active pharmaceutical ingredient (API). Additionally, CFD models were
developed using the Eulerian-Lagrangian framework, which included the Discrete Phase Model
(DPM) and turbulence models such as low Reynolds number (LRN) k-ω and Large Eddy
Simulation (LES) to simulate particle and airflow dynamics under realistic physiological
conditions. These models were validated against experimental data to ensure their accuracy and
reliability.
The initial project examined how airflow rate and spray cone angle affect aerosol deposition in an
adult model of the mouth and throat. It was found that recirculation zones at the 90˚ bend in the
oropharynx caused larger particles to be selectively retained. As airflow rates increased, the
aerodynamic size of the particles decreased, leading to better delivery to the distal airways.
However, larger cone angles resulted in more deposition in the mouth, while an 8˚ cone angle was
identified as optimal for minimizing particle loss in the upper airway. These findings emphasized
the importance of understanding the relationship between device parameters and inhalation
dynamics to enhance drug delivery efficiency.
The second part of the study examined the effects of constant and COPD-specific breathing
profiles under varying humidity levels, focusing on how these factors influence particle transport
and deposition. At low flow rates (30 L/min), there was a 39% increase in the deposition of large
particles on the airway walls. In contrast, high humidity levels (99%) allowed more large particles
(>5 μm) to pass through the airway, thereby reducing deposition in the mouth and throat. The
COPD breathing profiles caused a slowdown in the development of the aerosol plume, leading to
an increase in the deposition of large particles. Interestingly, regions of high turbulence, when
combined with humidity, resulted in a 4% reduction in the deposition of large particles. This
finding indicates complex interactions between environmental conditions and inhalation profiles.
The third study expanded the research to a pediatric mechanical ventilation model that simulates
a cystic fibrosis (CF) breathing profile. A 3D-printed airway derived from a CT scan was integrated
into an NGI to validate CFD simulations. The study focused on the mucus boundary conditions
using the Eulerian Wall Film (EWF) model and introduced a shear-thinning, non-Newtonian
mucus layer. The results indicated that transient airflow broadened the particle size distribution,
and the shear-thinning mucus disrupted the secondary flow, causing a more than 60% increase in
the minimum particle size exiting the trachea. Additionally, a synchronized actuation (t = 0 s) has
the highest deposition efficiency at 45.6%. Flow rate emerged as the most influential factor
affecting deposition patterns, as supported by a Morris sensitivity analysis
Tactile texture classification on uneven surfaces using a neural network soft voting ensemble
Full text linkWith the growing capabilities of intelligent robots in object recognition and manipulation,
the ability to sense and interpret physical contact through touch has become a
crucial component to enabling effective interaction with the physical world. Although
tactile texture classification on flat surfaces has been broadly studied in recent years,
uneven surfaces pose additional challenges due to variations in contact geometry and
surface normals. To address these challenges, this study introduces a new tactile texture
dataset comprising both flat surfaces and several distinct uneven surfaces, and
proposes a soft voting-based classification system built on deep neural networks, which
combines predictions from multiple temporal window sizes to improve robustness.
The dataset is collected using a compliant tactile sensor mounted on the end effector
of a UFactory Lite6 robotic arm that combines MARG and barometric data
for capturing dynamic contact interactions. The dataset includes six types of uneven
surfaces, each including a variety of textures to create diverse and challenging contact
conditions. To improve classification robustness and enable multi-scale analysis, the
time-series data are segmented using a sliding window approach with varying window
sizes. Multiple model architectures are trained on the windowed segments, including
1D Convolutional Neural Networks (1D-CNNs), Bidirectional Long Short-Term
Memory (BiLSTM) networks, hybrid 1D-CNN–BiLSTM models, self-attention-based
networks, and hybrid 1D-CNN–self-attention models. Their predictions are combined
using a soft voting strategy to enhance overall classification accuracy.
Experimental results based on 5-fold cross-validation demonstrate that self-attentionbased
models consistently outperform other individual architectures across all window
sizes. Moreover, the proposed voting system, which combines predictions from different
window sizes, further improves classification performance for all model types by
leveraging complementary temporal features.
This study demonstrates that combining deep neural networks with a soft voting
mechanism across multiple window sizes enables accurate tactile texture classification
on various types of uneven surfaces, contributing toward more robust and adaptable
robotic perception in complex environments
Loading-rate dependant fracture behavior of cemented paste backfill under curing pressure
No full textThis study investigates the loading-rate-dependent fracture behavior of cemented paste backfill (CPB) under varying curing pressures. CPB is widely used in underground mining to fill voids, and its mechanical performance is critical to ground stability and operational safety. While most laboratory testing is conducted under atmospheric conditions, CPB in the field cures under confining pressure, which can significantly affect its mechanical properties. To simulate real-world conditions, CPB samples were prepared and cured at pressures of 0, 29, and 58 psi, representing different backfill heights. Samples were tested at 7-, 28-, and 90-days using fracture mechanics-based tests under three different loading rates (0.1, 1, and 10 mm/min) across Mode I, II, and III fracture modes. Key parameters examined included material stiffness, fracture toughness, energy of crack initiation, and total energy of fracture.
The results demonstrated that both higher curing pressure and increased loading rate generally enhance the mechanical performance of CPB, with the most significant gains observed between 0.1 and 1 mm/min. Notably, stiffness and fracture toughness improved with curing time, while energy absorption was primarily governed by crack initiation. Auxiliary testing confirmed that increased curing pressure led to denser microstructure, slightly lower void ratios, and higher degrees of saturation. These physical changes likely contributed to the enhanced fracture behavior. The findings underscore the importance of considering both curing conditions and loading rate in the design and testing of CPB to ensure accurate predictions of field performance
The extent of tobacco consumption in the Indigenous population in association with pulmonary diseases in Canada
Full text linkObjectives: (1) To explore the prevalence of and characteristics associated with tobacco consumption in the overall Indigenous population and within specific demographic groups (e.g. age, sex, etc.). (2) To explore the association between tobacco consumption and COPD and asthma, in the Indigenous population, through the lens of the Integrated Life Course and Social Determinants Model of Aboriginal People's Health framework.
Methods: This cross-sectional study utilizes data from the Aboriginal People’s Survey (2017), with a sample of 20,849 self-identified Indigenous people living off-reserves across Canada aged 15 or older.
Results: The overall prevalence of smoking was 34.7%. The highest prevalence of smoking was seen in groups of people who drank 3+ drinks/week or every day (37.9%), had 3+ chronic diseases (37.3%). Individuals between 25-34 years old were 2.37 times more likely to be smokers (95%C.I 2.04- 2.75), those who experienced in-home smoking were 5.01 times more likely to smoke (95%, C.I 4.59- 5.47), people who feel a sense of belonging were 2.38 times more likely to smoke (95% C.I 2.18- 2.60), and individuals who consume alcoholic beverages three or more times a week or drink every day had a 23% higher likelihood of smoking (95% C.I 1.07- 1.41).
Overall, 13.2% of the study population reported having asthma, and 5.0% reported having COPD. Most of the participants with COPD were 55 years or older (11.4%) more individuals experienced in-home smoking (8.2%), 6.9% of smokers reported having COPD, and 22.6% had 3+ diseases. Smokers had a 52% higher likelihood of having COPD (95% CI: 1.31-1.76), participants 55+ years were 13 times more likely to have COPD (95% C.I: 7.94 -22.31), being female was associated with a 25% higher likelihood (95% C.I: 1.08-1.42), and in-home smoking was associated with a 59% higher likelihood (95% C.I: 1.36-1.9).
Fifteen percent (15%) of the participants who reported having asthma were female (15.2%), with 14% between the ages of 15-18, and 15% experiencing in-home smoking. Thirteen percent (13%) of people who reported asthma were smokers, and 14% reported three or more chronic conditions. Females had 49% higher likelihood of having asthma (95% C.I. 1.37-1.63), in-home smoking had a prevalence of asthma 25% higher (95% C.I: 1.11- 1.41), those who started smoking prior to 11 years old had a 50% higher prevalence of asthma (95% C.I: 1.06- 3.95).
Conclusions: This study found age and sex to have a significant relationship with smoking habits; women and people aged 25-44 years were more likely to partake in smoking. This highlights the need for a more targeted tobacco cessation program in this group to mitigate the impact of smoking-related adverse health effects for this group. In-home smoking very consistently has a significant association with the likelihood of individuals smoking themselves, as well as the likelihood of individuals having asthma or COPD. This emphasizes the need for policies targeting smoke-free homes to reduce the risk of diseases, particularly for young children within the Indigenous population
A process design for the purification of carbon contaminated with Cu-Bi alloy from catalytic methane decomposition
No full textLow-carbon hydrogen production by catalytic methane decomposition (4→2()+()) has demonstrated potential to significantly decarbonize industrial sectors. Previous research has proposed carrying out the reaction in a liquid metal bubble reactor containing catalytic molten metal alloys such as Cu0.45Bi0.55 to allow hydrogen bubbles to exit through the top while the solid carbon product floats to the top of the melt to be skimmed or removed by other mechanical means. Metal lost in the process of carbon removal can impact the plant profitability because it will need to be continually replenished. Additionally, metal contaminants in the carbon product pose limitations on its ability to be sold as carbon black, and on its ability to be stored permanently due to the risk of metal contaminants in the environment. In this work, the process design methodology for the purification of carbon contaminated with copper and bismuth from catalytic methane decomposition is presented along with the capital costs of carbon processing equipment. Bismuth has a relatively high vapour pressure, so it is removed by vacuum distillation. A mass transfer model is applied to a lift-spray apparatus wherein the molten mixture of copper, bismuth, and carbon is sprayed up through a riser into a vacuum chamber where the bismuth vapours can be condensed and recovered. The spray creates smaller droplets which help increase the amount of surface area available for bismuth to evaporate. Copper is removed by leaching in a sulfuric acid solution by ()+2++0.52 →2++2. The carbon product is then filtered and rinsed from the leaching solution before being dried in a rotary dryer. Copper is precipitated from the filtrate solution using scrap iron, a metal higher in the electromotive series, in a process called cementation. Copper particles can be filtered from the solution and then sold as lower grade copper due to some iron contamination in the copper. The final carbon product is 98.9 wt% carbon on a dry basis, which meets the specifications for rubber-grade carbon black. The cost of carbon processing equipment per tonne of hydrogen produced is estimated at 1500-8000 USD/tonne H2. This work creates a pathway to recover metal catalyst lost in the process of carbon removal from methane decomposition in a liquid metal bubble reactor. The purified carbon product can be sold on the carbon black market or safely stored underground
The SHINE (Supporting Her In Navigating Exercise) Program: an experimental study examining peer support as an exercise promotion tool among undergraduate women initiates
Full text linkBackground: Despite the benefits of regular exercise, many Canadians, especially undergraduate women (UW), experienced decreased engagement throughout the pandemic, due, in part, to feelings of low social support and confidence. One promising approach to enhance participation is peer-mentorship programs (PMP): pairing knowledge-seeking individuals with experienced mentors. To date, theoretically grounded research on PMP tailored to UW remains sparse. Objective: Grounded in self-determination theory (SDT), this study examined the impact of a 6-week, campus-based exercise PMP on psychological outcomes and adherence among UW initiates. All participants were expected to improve all outcomes, with greater gains in the PMP group. Method: Undergraduate women from a mid-sized Canadian university wanting to increase activity were randomized to intervention or control groups. Senior students in a health discipline with exercise expertise were recruited as mentors and participated in a 2-hour, motivational interviewing focused training workshop. All participants received a standardized campus gym tour, a structured exercise guide, and were asked to exercise triweekly. Once a week, mentors exercised with their intervention participants and offered ongoing virtual support. In addition to demographic data, quantitative data were collected pre-, mid-, and post-intervention through the Psychological Needs Satisfaction in Exercise Scale (PNSES), Behavioural Regulation in Exercise Questionnaire-3 (BREQ-3), and Depression Anxiety Stress Scale- Short Form (DASS-21). Exercise adherence was captured through Strava and software-supported facility attendance. To gain insights into study experiences, post-program participants completed an exit questionnaire to gain insights into their study experiences. Quantitative data were analyzed using descriptive statistics and two-way mixed factorial ANOVAs; qualitative data were inductively and deductively analyzed. Results: Eighty prospective participants were assessed for eligibility, and 33 were randomized to the two conditions. In total, 26 UW completed the intervention or at least two of the three assessments (intervention = 13; control = 13). Intervention participants were supported by one of the six program mentors. Demographic data identified that participants were an average of 24.3 years old (SD = 12.7), most (46%) were enrolled in their first year of university and were classified as having overweight (Body mass index; M = 25.5, SD = 5.6). Quantitative results found interaction effects (p < 0.05) for autonomy and competence, as supported by qualitative accounts. Both groups experienced significant improvements to external, identified, and integrated regulation, along with symptoms of depression, anxiety and stress. Discussion: The current PMP proved to be an effective method for enhancing autonomy and competence among participants with a mentor, with additional improvements in other constructs. Taken together and in line with the literature, these results highlight the value of tailored, supportive exercise intervention for promoting UW exercise engagement. This population stands to gain from greater access to exercise opportunities, given the well-established physical and mental benefits associated with more movement. Remarkably, increases in most basic needs, regulation, and distress symptoms emerged in as little as 3 weeks: a novel finding that warrants further exploration, particularly regarding the mechanisms behind these early changes. Based on these findings, future programs should continue exploring accessibility, early engagement, and adaptable delivery methods in longer programs. Conclusion: Effective strategies to promote UW exercise habits are essential for improving quality of life and fostering lifelong habits. Strengthening campus movement culture benefits physical and mental health during this critical developmental phase. Results will be shared with key stakeholders, such as Lakehead Athletics and Student Health and Wellness to inform best practice