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Demographic processes and behaviour of snapping turtles (Chelydra serpentina) in the context of past catastrophes and ongoing threats
No full textLifetime patterns of somatic growth, reproduction, and survival comprise life history, which links
individual traits to the vital rates that determine the properties of populations, such as generation
time, potential rate of increase, and responses to environmental perturbation. Individual lifehistory traits, such as survival, age at first reproduction, reproductive frequency, and the size and
number of offspring covary along a limited number of dimensions forming the pace-of-life
continuum because they are tightly linked by trade-offs and constraints. Furthermore, variation in
life history also covaries with morphological, physiological, and behavioural traits.
This dissertation focuses on interconnectedness of life-history traits with social behaviour,
population dynamics, and conservation. The Algonquin long-term field study of Snapping Turtles
(Chelydra serpentina) provides a unique opportunity to analyze these relationships in a longlived organism with a slow life history by building upon a productive foundation of previous
research. Turtles‘ slow life history, low and variable juvenile recruitment, and reliance on high
adult survivorship makes them vulnerable to anthropogenic threats resulting in turtles being
disproportionately imperilled.
In Chapter 1, I analyzed the patterns of abundance and survival during and after a population
catastrophe and revealed individuals transitioning between sites in a connected population but no
recovery over 23 years. Because of their cryptic behaviour, the mating system of Snapping
Turtles was poorly known, so in Chapter 2 I quantify sexual size dimorphism and frequency of
wounds to infer patterns of intraspecific aggression consistent with a mating system mediated by
male combat. The third chapter focused on the somatic growth component of life-history by
refining growth modelling by developing a model of seasonal variation in growth rates. In
Chapter 4, I examine the demography of Snapping Turtles dispersing across roads by testing
hypotheses based on the mating system revealed in Chapter 2 using a demographic model
parameterized with survivorship estimated in Chapter 1 and the growth modeling approach
developed in Chapter 3. I show that juveniles are overrepresented on roads and face higher
mortality risk and that the lost reproductive value of juveniles killed on roads contributes
substantially to the overall burden of road mortality in this long-lived species.Doctor of Philosophy in Boreal Ecolog
An exploration of experimental and numerical approaches to design of a ducted helical air turbine
No full textThe proposed device is a ducted air turbine with a 2-bladed helical rotor. To attempt to characterize the performance
of the device, as well as establish a methodology for further experimentation, a campaign of testing was undertaken.
The campaign described in the work culminates in a comparative study between a simulated experiment (undertaken
using Computational Fluid Dynamics) and a physical experiment (undertaken with a dynamometer, and a duct system
connected to a flow meter and centrifugal air pump). The simulated experiment has been transformed using the
similarity laws, and the resulting data has been used to predict the performance of the physical experiment by
interpolating to the setpoints observed in the physical experiment. These setpoints are defined (in both the simulated
and physical experiments) by experimental input variables: bulk flow velocity of the fluid, and rotational velocity of
the rotor. Each successful experiment produces experimental output variables: braking torque applied to the rotor,
and pressure drop across the duct section which encloses the rotor.
A direct comparison of simulated and physical performance data through the use of nondimensional
coefficients demonstrates good agreement between the two experiments, though some discrepancy in torque has
been identified. The degree of agreement suggests that this implementation of CFD and the similarity laws would be
a good basis for future analysis of turbine performance.Master of Applied Science (MASc) in Engineering Scienc
Geology, mineralogy, geochemistry, and petrogenesis of Ni-Cu-(PGE) and PGE-(Cu)-(Ni) deposits in China
Get PDFNickel, copper, and platinum-group minerals are regarded as “Critical Minerals” that are crucial to the
national economy and sustainable development. Magmatic sulfide deposits account for approximately
93% of Chinese nickel resources, 7.3% of Chinese copper resources, and more than 90% of Chinese
platinum-group element resources. This study focuses on the mineralogy, geochemistry, and isotope
geochemistry of magmatic sulfide deposits in China, including detailed studies of the Jinbaoshan and
Bamazhai deposits in the Emeishan Large Igneous Province, leading to a metallogenic model for the
spectrum of magmatic sulfide deposits in China.
The 260 Ma Jinbaoshan platinum-group element (PGE) deposit in SW China is a sulfide-poor magmatic
PGE deposit that experienced multiple phases of post-magmatic modification. It is characterized by: 1)
high-temperature violarite-pyrite1-millerite-chalcopyrite and 2) low-temperature violarite-(polydymite)-
pyrite2-chalcopyrite assemblages with more than 16 varieties of platinum-group minerals. Postmagmatic hydrothermal fluids enriched the mineralization in lead, silver, cadmium, and zinc. Cobalt and
platinum were also added into violarite, and expelled palladium to the margins of high-temperature
violarite and millerite, which also caused the formation of pallidum-enriched minerals. Late-temperature
violarite inherited palladium, rhodium, iridium, and osmium from primary pentlandite. Overall, the
atypical sulfide assemblages in Jinbaoshan deposit result from multiple overprinted post-magmatic
processes, but they did not significantly change the platinum-group element contents of the
mineralization, which is interpreted to have formed at high magma:sulfide ratios (500~50000) through
interaction of crustal sulfide and a hybrid high-magnesium magma derived by melting of a modified
region of the Earth’s mantle.
The ~259 Ma Baimazhai nickel-copper-(platinum-group element) deposit is a typical magmatic sulfide
deposit in Emeishan Large Igneous Province. The economic No. 3 intrusion is lenticular and
concentrically-zoned from finely dispersed through “net-textured” to massive sulfides (margin to core).
The sulfide assemblage comprises pyrrhotite, chalcopyrite, and pentlandite, with lesser magnetite,
cobaltite, violarite, and galena. The mineralization is enriched in nickel, copper, and cobalt relative to
platinum-group elements. Combined with the geochemical features of Baimzhai host rocks, the sulfides
appear to have formed from a PGE-depleted magma derived from mantle source that was modified by crustal contamination and formed at moderate magma:sulfide ratios (100–1000). Post-magmatic
alteration modified the primary sulfide assemblage, resulting in secondary sulfides enriched in nickelcobalt and antimony-lead-silver-gold. The tectonic and petrogenetic settings of Baimazhai and other
deposits in China highlight the potential of nickel-copper deposits to occur in post-subduction settings
and exploration potential remains for the Ailaoshan orogenic belt to host additional magmatic sulfide
deposits.
Unlike other magmatic sulfide deposits in the world, many of which are older and formed primarily in
extensional settings, all known Chinese deposits are younger and many are inferred to have formed in
compressional settings. Mineral chemical, whole-rock geochemical, ore geochemical, and isotopic data
for 18 typical deposits have been used to aid in the assessment of their genesis and prospectively. Most
deposits in mountain belts appear to have been derived from magmas formed by partial melting of a
modified but originally PGE-depleted mantle source with minor crustal contamination. Most deposits in
the Eemeishan Large Igneous Province appear to be hosted by rocks derived from magmas generated
from originally more enriched mantle sources with variable degrees of crustal contamination. Deposits
related to the breakup of Rodinia exhibit transitional geochemical characteristics. Taken together with
the geochemical and isotopic evidence, it is suggested many Chinese magmatic sulfide deposits were
derived by melting modified mantle, most likely produced by interaction of recycled oceanic crust with
depleted asthenospheric mantle.Doctor of Philosophy (Ph.D.) in Mineral Deposits and Precambrian Geolog
Digesting Ozempic: How information sources on the type 2 diabetes drug Ozempic can affect patient understanding and decision making
No full textMajor Research Paper in Science Communication.Supervised by Dr. Chantal Barriault and Dr. Jeff Gagnon.The growing prevalence of type 2 diabetes mellitus (T2DM) has been accompanied by the development of new medications for treating the condition. One such medication is semaglutide, which has been extensively discussed in the media under its brand name Ozempic due to its potential for causing weight loss. Amidst the growing discourse surrounding Ozempic, alongside evidence that patient information sources can be inaccessible or unreliable, the research question addressed here is: how is the framing of information on Ozempic, from passive and active information sources, impacting how patients with T2DM in Canada come to understand and make decisions regarding their health? The approach to answering this question involved collecting artifacts from passive and active information sources, before performing first a content then closer rhetorical analysis to discover which frames, or terministic screens, were employed. It was observed through this analysis that passive sources like news and social media often exclude much of the science behind Ozempic to focus on the weight loss discourse. These sources also sometimes provide inaccurate scientific information, which can be misleading to patients. The active sources like websites and pharmacy handouts, meanwhile, cover more, though not all, of the science behind Ozempic, but their complexity and structure can make the information more difficult to comprehend. Overall, it is clear that no single source provides comprehensive coverage of Ozempic to allow T2DM patients to make informed decisions, and even spread across multiple source types, gaps remain that need to be addressed.Master of Science Communicatio
Thermal transport in kinked nanowires through simulation
No full textThe thermal conductance of nanowires is an oft-explored quantity, but its dependence on the nanowire shape is not completely understood. The behaviour of the conductance is examined as kinks of varying angular intensity are included into nanowires. The effects on thermal transport are evaluated through molecular dynamics simulations, phonon Monte Carlo simulations and classical solutions of the Fourier equation. A detailed look is taken at the nature of heat flux within said systems. The effects of the kink angle are found to be complex, influenced by multiple factors including crystal orientation, details of transport modelling, and the ratio of mean free path to characteristic system lengths. The effect of varying phonon reflection specularity on the heat flux is also examined. It is found that, in general, the flow of heat through systems simulated through phonon Monte Carlo methods is concen- trated into a channel smaller than the wire dimensions, while this is not the case in the classical solutions of the Fourier model.Natural Sciences and Engineering Research Council of Canada (RGPIN/6563-2018), Laurentian University, Ontario Graduate Scholarship progra
Using stable water isotopes and isotope-enabled hydrologic modelling to quantify water in Central and Northeastern Ontario
No full textThe understanding of hydrologic processes in Central and Northern Ontario's mesoscale watersheds, located within the Precambrian Shield region, remains limited, posing challenges for accurate hydrological modeling and assessment of climate change impacts on water resources. This study focuses on Central and Northeastern Ontario, typically characterized by granitic bedrock, small depressions, and shallow acidic soils, where annual precipitation exceeds evapotranspiration, resulting in abundant surface waters. Changes in hydrological processes in this region can have significant consequences for the local ecosystem of mesoscale watersheds. Therefore, investigating the effects of climate change on water quantity is crucial. This research utilizes stable water isotopes (SWIs) as cost-effective tools to improve our understanding of hydrologic processes and flowpaths in mesoscale Precambrian Shield watersheds. By analyzing long-term meteorological, hydrometric, and SWI data from the Sturgeon River, French River, and Muskoka River watersheds, valuable insights are gained regarding the impacts of climate change on hydrological processes in these regions. The study employs a new isotope-enabled distributed hydrologic model, isoWATFLOOD, which provides a good representation of fluxes, storages, and their changes due to climate change in mesoscale and large- scale watersheds. The research objectives include exploring the key controls and importance of surface water storage (lakes and wetlands) on hydrologic function in the Sturgeon River-Lake Nipissing-French River (SNF) and Muskoka watersheds, evaluating isoWATFLOOD hydrologic model's performance in simulating streamflow and isotope values in the Sturgeon River-Lake Nipissing (SN) watershed, evaluating the importance of wetland connectivity representation in isoWATFLOOD performance across the SN watershed, and assessing the impacts of climate change on streamflow and hydrologic partitioning in the SN watershed using the isoWATFLOOD hydrologic model. PCA and HCPC approaches are used to identify variation in controls on hydrologic function in SNF and Muskoka watersheds using combination of hydrometric, geology, landscape and isotopic metrics. The findings reveal greater evaporative enrichment impacts in Muskoka compared to the SNF catchments, with Muskoka exhibiting less variability in streamflow isotopes. The study identifies a positive correlation between wetland area and damping ratio (coefficient of variation of isotopes in streamflow to coefficient of variation of isotopes in precipitation), suggesting that wetland connection/disconnection and varying evaporation impacts contribute to isotopic value variability in catchments with higher wetland coverage. Muskoka and SNF catchments generally fall into separate clusters, primarily influenced by wetland and lake area percentages, mean slope, and the extent of glacialacustrine and glaciofluvial outwash deposits. The combination of catchment classification analyses and stable isotopes (δ 18O and δ 2H) proved effective in studying how different catchment characteristics influence variations in hydrometric response. An application of isoWATFLOOD was set up for Sturgeon River-Lake Nipissing (SN) watershed. Five separate models with varied connected wetland (CW) ratios between 10% to 50% are set up to evaluate the importance of CW ratio in model performance. The SN isoWATFLOOD model, calibrated using isotope and streamflow data, successfully simulates streamflow and isotope values (KGE > 0.6) across 11 catchments. Wetland connectivity percentage significantly influences streamflow and isotope simulations, particularly during the calibration period. The most accurate streamflow simulations occur with 40% wetland connectivity, improving baseflow representation. This study advances isotope-enabled hydrologic simulations using isoWATFLOOD and provides insights into wetland connectivity representation, a critical landscape aspect of Precambrian Shield watersheds. Stable isotopes prove valuable in addressing the challenge of equifinality. Using the SN isoWATFLOOD model and considering 16 global climate model (GCM)- emission (RCP) models, findings project a future characterized by warmer and wetter climatic conditions (2020-2082) compared to the baseline period (1990-2019). On average, the study predicts an annual discharge increase ranging from 4.8% to 11.5%, with elevated winter and fall streamflow across the watershed. These changes result from warmer fall and winter seasons, reduced freezing days, increased annual precipitation, and more frequent extreme precipitation events. Additionally, the simulations indicate an earlier spring freshet peakflow, accompanied by a reduced peak flow rate. Furthermore, climate change will impact hydrological partitioning, leading to alterations in the contributions of annual average daily baseflow to streamflow. Moreover, there will be a rise in average annual daily direct runoff due to intensified annual precipitation, more frequent extreme precipitation events, and rain-on-snow occurrences within the watershed. The results highlight the significance of integrating climate change impacts into water resources management planning, specifically concerning peak flow timing, seasonality, and changes in flow volume during different seasons
Super-resolution image reconstruction from multiple low-resolution images
No full textThis study explores a novel approach for super-resolution image reconstruction from
multiple low-resolution images, employing frequency domain motion estimation technique
(FMT), Keren-based image interpolation, and bicubic interpolation (BI). The method
performs well in estimating scaling parameters, but accuracy decreases as shift distance or
rotation angle increases. Compared to Vandewalle's algorithm, the proposed method shows
better accuracy in estimating scaling parameters but similar accuracy for rotation and
translation parameters. Differences are observed in estimated values for each parameter
between both methods. The study underscores the need for further research to improve the
accuracy of the proposed method in motion estimation and interpolation optimization.
Additionally, Generative Adversarial Networks (GANs) outperform Bicubic and Wavelet
Domain Super-Resolution (WDSR) algorithms in image quality improvement, indicated
by higher Peak Signal-to-Noise Ratio (PSNR) values. This superior performance is
attributed to GANs' ability to leverage deep learning algorithms to capture complex image
features. The research validates the potential of the proposed method for super-resolution
image reconstruction, and the power of deep learning-based algorithms, specifically
GANs, in enhancing low-resolution images. More advanced motion estimation algorithms
and interpolation technique optimization could further improve the accuracy of this
method.Master of Science (MSc) in Computational Science
sno+ background study: polonium on acrylic vessel surface and radon assay
Get PDFSNO+ is a 780 tonnes organic liquid scintillator neutrino detector located at Vale’s
Creighton mine, Sudbury, ON. 2 km overburden of rock above helps to achieve the low
cosmic radiation background level of SNO+. Meanwhile, radioactive material in the rock
can decay and produce radiation in the region of interest for the search of 0νββ decay. SNO+
is looking for neutrinos at very low energy and thus it is crucial to have a low background
environment. My thesis evaluates two kinds of background sources: 222Rn and 210Po. 222Rn
is the progeny of 238U in the rock. The water and gas assays are used to monitor the 222Rn
concentration in the surrounding cavity water and other parts of the experiment or other
gas volumes in SNOLAB. The analysis of the SNO+ data helps to understand the 210Po
activity on the internal surface of the detector’s acrylic vessel. The 222Rn level in the cavity
water is below the target of 4.5 × 10−13 gU238/gH2O. The Rn levels in the LN2 plant and
international dewar are at a 10−4
reduction factor compared to mine air. The 210Po background level in the internal AV is holding a relatively constant level of about 1800 events
per second. Spatially, the 210Po backgrounds are more active at the equator and the belly
plate regions. The estimated number of 210Pb atoms deposited on the AV inner surface is
1.84 × 1012
.Master of Science (MSc) in Physic
Écotourisme et revalorisation des traditions vernaculaires de la commune rurale de l’Oukaimeden: du tourisme de masse vers un tourisme rural
No full textCette thèse porte sur l’écotourisme, une approche
responsable qui cherche à trouver l’équilibre entre
la durabilité environnementale et le développement
économique de l’industrie touristique. Un alternatif
au tourisme de masse non durable, l’écotourisme
est surtout important dans les régions pauvres
convoitées par les touristes. La thèse se concentre
sur le village de l’Oukaimeden au Maroc, où le
tourisme saisonnier pour la classe moyenne ne
profite pas aux villageois. L’objectif est de promouvoir
le tourisme durable multi-dimensionnel toute l’année
à travers une intervention architecturale et paysagère
spécifique pour le village, visant à améliorer les
conditions de vie des habitants, tout en protégeant
l’environnement. Cette intervention se base sur un
programme global de création d’emplois locaux et
de mise en place de circuits touristiques éducatifs
en se basant sur des stratégies vernaculaires. Ces
mesures valoriseront les atouts naturels et culturels
du village pour sensibiliser les touristes à l’écologie et
bénéficier les villageoisMaîtrise en architecture (M.Arch
Prediction of drug targets for pancreatic cancer using machine learning techniques
Get PDFPancreatic cancer is one of the deadliest cancers with a very low survival rate. However, people
who are diagnosed early have much longer survival than the ones who are not diagnosed with early
screening. Therefore, the importance of early diagnosis and consequently, the treatment of
pancreatic cancer can be understood. As pancreatic cancer is rare, early screening for pancreatic
cancer is extremely costly. Research has been going on to find such techniques that can detect and
hence diagnose pancreatic cancer early through Machine Learning models and use them even for
the prediction of survival, Immunotherapy response, risk of re-occurrence, etc. The successful
implementation of this technology in the prediction of the presence of pancreatic cancer is a
breakthrough as it will greatly increase the survival rate as well as the life expectancy of such
patients. One of the major challenges in the treatment of pancreatic cancer is the lack of specific
and effective drug targets. In recent years, advances in our understanding of the biology of
pancreatic cancer have led to the identification of several potential drug targets, including
oncogenic signaling pathways, and cellular metabolism. Pancreatic cancer cells are highly
metabolic, relying on glycolysis and the citric acid cycle to generate energy. Inhibiting these
metabolic pathways has been shown to reduce the growth and survival of pancreatic cancer cells
in preclinical studies. Pan-Cancer dataset from Genomics of Drug Sensitivity in Cancer (GDSC)
was used in this research to predict drug targets. In this study Machine Learning algorithms were
used such as feature importance using Random Forest, prediction of Drug Targets using Bagging,
Dense Neural Network, Naïve Bayes, Multilayer Perceptron, K-Nearest Neighbors, Support
Vector Machines, Long Short-Term Memory, Recurrent Neural Network and XGBoost classifier.Master of Science (M.Sc.) Computational Science