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Investigation and identification of Ediacaran microbially induced sedimentary structures (MISS) in Fermeuse and Trepassey Formation, Newfoundland
No full textMicrobially induced sedimentary structures (MISS), the physical sedimentary structures shaped and modified by microbial activities, that were abundant during Ediacaran. Their significance extends to the indicators of the depositional environments to potential hints at the contribution of microbial mats to the preservation of soft-bodied organisms. However, despite their significance, Ediacaran MISS remain understudied, with many structures yet to be confidently classified.
This thesis investigates two Ediacaran MISS candidates—Arumberia and bubble trains—identified in sedimentary rocks from Musgravetown and St. John’s group in Newfoundland. Petrographic analysis, supplemented by geochemical and morphological observations, reveals that their formations are influenced by palaeocurrents and exhibit Microbially Induced Sedimentary Textures (MIST), confirming their MISS origin.
Moreover, Arumberia consists of multiple morphotypes shaped by varying hydrodynamic and environmental conditions, suggesting that they worked as stimuli to form each Arumberia morphotype. Bubble trains, on the other hand, result from patchy microbial mat growth on the seafloor, which facilitates gas trapping. The accumulation of gas beneath these mats led to the formation of circular depressions at the sediment-mat interface. As such, bubble trains reflect the localised distribution of microbial mats and their role in trapping gas. By integrating sedimentological, geochemical, and morphological data, this study suggests the classification of these structures as MISS and enhances our understanding of its formation in Ediacaran environments
Too close for comfort: opposition strategies against authoritarian co-optation in Turkey and Hungary
No full textAuthoritarian rulers legitimize the regime and survive by not only repression but also tempting opposition parties into alliances. Yet, only some parties accept co-optation while others resist. While most co-optation scholarship focuses on regime incentives and calculus, I examine the opposition's characteristics: ideological distance and radicalism, as well as their impact on the decision to accept or resist co-optation. Using a most similar systems design, I focus on far-right party policies of Turkey (2011-2018) and Hungary (2010-2018), to compare co-optation calculus. To explain why Turkey's MHP accepted co-optation while Hungary's Jobbik resisted, I show that co-optation hinges on opposition party characteristics, namely ideological distance to the autocrat and radicalism, together with country- and party-specific circumstances. The results suggest that the MHP's ideological radicalism and proximity to the AKP created a dependence on an alliance, prompting acceptance, whereas Jobbik's moderation and ideological distance from Fidesz insulated it, reinforcing resistance. Differences in political pressure, organizational extensiveness, and electoral support further conditioned these outcomes and co-optation calculus. By focusing on opposition agency in authoritarian co-optation, I refine co-optation theory beyond regime incentives and calculus. This study identifies causal mechanisms linking ideology, radicalism, and organizational context to divergence in response to co-optation by presenting a deeper analysis of country- and party-specific conditions
The effect of arm locomotor behaviour on spinal motoneuron excitability innvervating the stationary leg
No full textSerotonin’s role in enhancing motoneuron excitability via persistent inward currents is well-established in reduced preparations, but its widespread effects on human motor control, specifically across limbs, is less understood. The aim of this study was to address whether monoamine release helps mediate state changes in motoneuron excitability during remote locomotion in humans. To achieve this, we assessed whether rhythmic arm movement promotes alters motoneuron excitability in stationary legs. Large populations of motor units were identified during slow isometric contractions of the tibialis anterior using high-density surface electromyography in conjunction with a convolutive blind source separation algorithm. Results indicated that recruitment and derecruitment thresholds were unaffected by arm cycling, but ΔF, a key estimate of the contribution of PICs to motoneuron discharge, was reduced during arm cycling conditions. Further assessment of the ascending discharge rate profile revealed that brace height (BH), an indirect indicator of neuromodulatory drive, increased during both cycling conditions. Taken together, the effects on ΔF and BH together suggest enhanced neuromodulatory drive alongside increased or altered patterns of inhibitory input. These findings indicate that locomotor activity of the upper limbs produces a complex interplay of excitation and inhibition to motor pools in the legs, which advances our understanding of interlimb neural coupling
Receiver algorithms for next-generation wireless communication networks
No full textIn a rapidly evolving technological era, wireless communications have become indispensable,
playing a pivotal role in almost every aspect of our daily lives. The burgeoning
demand for enhanced user experiences and the proliferation of mobile devices require
innovative techniques to improve the performance and capacities of future wireless
communication networks. To this end, numerous speculative studies and technological
discussions have emerged as the world anticipates the launch of the sixth-generation
(6G) wireless networks at the end of the decade. 6G networks are expected to support
numerous applications beyond the traditional communication services hitherto enabled
by wireless networks. In order to reduce their carbon footprint and achieve the vision
of global connectivity, 6G networks must also be energy-efficient.
Hence, there is a need for innovative algorithms and frameworks for signal transmission
and processing. This thesis focuses on processing the received signal in some envisioned
scenarios for 6G networks.
A low-complexity joint signal processing scheme is presented for an uplink terrestrial
reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication
(ISAC) system. ISAC is a spectrally and hardware-efficient design paradigm that
enables the coexistence of communication and radar-sensing functionalities. The RIS—
made up of nearly passive, low-cost materials—is used to enhance the performance of
the ISAC system. In an interference cancellation (IC) framework, the joint received
signal is reformulated to enable the use of a search-tree (ST) for communication
signal processing. The K-best algorithm (KBA) is deployed within the ST to detect
the communication signal. After detection, the IC-based minimum mean-squared
error (MMSE) estimation technique is used to calculate the sensing parameters of
the radar target in the ISAC system. Based on a comprehensive study of the KBA’s
computational complexity and simulation results, it is observed that the KBA achieves
near-optimum performance while offering noticeable savings in complexity. This
indicates a high computational efficiency by the proposed KBA. The MMSE technique
shows improved estimation performance in the presence of RIS.
Considering the important vision of global coverage in 6G networks, this thesis
also introduces a satellite-terrestrial integrated network (STIN)-ISAC-RIS scenario.
Integrating broad-coverage satellite systems into high-speed terrestrial networks in
6G is an innovative means of ensuring reliable connectivity in remote areas. In a fullduplex
setup, the terrestrial component of the STIN incorporates an uplink ISAC-RIS
scenario while the satellite transmits downlink signals to the terrestrial ISAC base
station. The maximum likelihood (ML) detection algorithm is proposed to jointly
detect the terrestrial and satellite communication symbols. After reformulating the
MMSE estimator for the STIN-ISAC-RIS system, it is used to compute the reflection
coefficients of the terrestrial ISAC target. The computational complexities of the ML
for joint detection and MMSE algorithms are analyzed in terms of the number of
real additions and real multiplications. It is noticed from the results and complexity
analyses that the ML achieves optimum detection performance at a high complexity,
whereas the MMSE estimator obtains a good estimation performance in the presence
of RIS at low complexity. The STIN-ISAC-RIS system is also observed to show
considerable improvement in performance when the number of optimized RIS phase
shifts in the terrestrial network is increased
Watchman's walk on products
No full textThe watchman's walk problem is concerned with finding a shortest walk through a
museum, starting and ending at the same point, such that such that a guard either
visits or peers into every room. That is fi nding a minimum closed dominating walk.
The length of this walk is the watchman number. In this work, we study the watchman
number of the strong, categorical and lexicographic products of graphs. For the strong
product we study the watchman's walk of arbitrary graphs, cycles and we give several
bounds. We also consider the watchman's walk for the categorical product of graphs
and we discuss some families of graphs such as complete graphs and cycles. We also
give upper bounds for the watchman number of arbitrary graphs. Finally, we consider
the lexicographic product and we completely characterize the watchman number
Fine gradings on associative superalgebras with superinvolution over an algebraically closed field
No full textAssuming that the ground eld is algebraically closed and of characteristic not equal
to 2, we classify, up to equivalence, the ne gradings on nite-dimensional associative
graded-simple superalgebras with superinvolution. Our approach relies on Wedderburn
structure theory for associative graded-simple superalgebras satisfying the
descending chain condition on graded left ideals. This framework naturally leads to
the study of nondegenerate sesquilinear forms associated with superinvolution. To
address the equivalence problem, we construct explicit models that are equivalent to
the given graded-simple superalgebras and analyze the conditions under which such
models are themselves equivalent
The gut-brain connection: probiotic supplementation to alleviate cognitive decline and inflammation in rodent models of pretangle tau and stress
No full textThe microbiota-gut-brain axis is a crucial link to peripheral and central nervous systems, with
gut health implicated in health and disease, including Alzheimer’s disease (AD) and stress. The
objective of this dissertation is to explore the role of strengthening the gut microbiota in brain
health and early-AD pathologies.
First, I will investigate the effects of probiotic supplementation on cognitive function, brain
inflammation, and gut microbiota composition. We employed a locus coeruleus
hyperphosphorylated pretangle tau rat model, which closely resembles preclinical AD. Rats with
pseudophosphorylated human tau in the LC showed deficits in spatial and olfactory learning,
increased microglia and astrocyte activity, blood-brain barrier (BBB) leakage, and elevated
peripheral inflammation. Probiotic supplementation increased gut microbiome diversity,
optimized bacterial composition, and ameliorated cognitive deficits. A reduction in inflammation
and glycogen synthase kinase 3 beta (GSK-3β) activity in the hippocampus of female rats was
observed, suggesting gut health modulation as a potential therapeutic strategy in preclinical AD,
and providing a possible mechanism underlying AD sex differences.
Second, I examined the effects of probiotics prior to chronic stress or enrichment on cognitive
function and brain health. Probiotics prevented stress-induced spatial memory impairments and
enhanced learning under enrichment conditions. We propose this is linked to increased gut
microbiome diversity and eubiosis, which was observed in our animals. Probiotics prevented
increased levels of the microglia marker ionized calcium-binding adaptor molecule 1 (Iba-1)
found in stressed rats and showed differences in BBB integrity and tyrosine hydroxylase (TH)
levels in the hippocampus between stress and enrichment groups, with beneficial effects
observed in enriched animals.
These findings highlight the potential of probiotics to enhance cognitive function and brain
health through modulation of the gut microbiota, offering a non-invasive therapeutic approach
for AD and stress-related cognitive decline.Includes bibliographical references (pages 130-161
Feasibility study, design, dynamic modelling, simulation, and control of a solar-powered sucker rod oil pump
No full textAs conventional oil and gas facilities continue to age, stripper wells and marginal field operations
are increasingly suspended, orphaned, and abandoned at an alarming rate. In remote and isolated
facilities, the deployment of onsite renewable energy and low-cost, open-source communications
systems is an increasingly promising trend for sustainable and reliable management of onsite
operations. Throughout this research, a 100% renewable energy-powered microgrid is proposed
for driving a remote oil well located in the city of Medicine Hat, southeastern Alberta, Canada.
Two different oil and gas production system simulators: Quick Rod (QRod) and Production System
Performance Analysis Software (PROSPER), are adopted to determine the optimal rating of the
electric motor that can reliably drive the sucker rod pump. A parametric investigation is first
performed in QRod, and the result is then integrated with the PROSPER workflow to minimize
the iteration time and produce a more efficient electric motor sizing. The load applied by the pump
on the rod string is determined in QRod by specifying the target production rate; and performing
a parametric investigation to determine the impact of changing parameters (such as stroke rate,
stroke length, and pump diameter), on the overall output torque on the polished rod and rod string
loading, ultimately obtaining the minimum rating of squirrel cage electric motor required to serve
as the prime mover for the remote oil well.
The research then extends to the novel application of off-grid renewable energy systems for
powering artificial lift in remote oil facilities. Considering the load profile of the producing oil
well and Utilizing HOMER Pro software, the study evaluates various renewable energy
architectures of solar PV, wind turbine, and battery storage systems for both intermittent and
continuous pumping scenarios. The feasibility study for the optimal sizing, technical, and
economic feasibility of a renewable energy system for a remote oil well is performed. Two viable
alternatives are proposed, one based on cost minimization and the other based on minimization of
unmet load. The most economical solution for repurposing idle wells at the selected remote
location is identified as a system comprising solar PV and battery storage with intermittent
pumping, offering a sustainable and cost-effective alternative to well abandonment and
decommissioning.
To enhance remote monitoring and control capabilities, a low-cost, open-source, Supervisory
Control and Data Acquisition (SCADA) system based on Node-RED and Arduino
microcontrollers was developed. This Internet of Things (IoT) based system comprises a main
terminal unit, a remote terminal unit, and a local server, which is integrated with various sensors
and transducers for comprehensive data collection, including accelerometer, temperature, flow
rate, water level, voltage, current, and distance measurements. A web-based graphical user
interface (GUI) is developed in Node-RED for data collection, logging, and visualization. To
facilitate communication between the server and the client, Nginx is adopted as the proxy server
between the local server and the router, to implement Hypertext Transfer Protocol, ensuring loadbalancing
and basic access authentication.
To gain deeper insights into the behavior of the overall system and predict the response to various
environmental and operating conditions, design, dynamic Modelling, simulation and control is
perfomed in Simscape. The load Modelling of the sucker rod pump which entails hydraulic, and
mechanical domains is first developed, followed by solar-powered microgrid modelling and
simulation. The outcome of the research is an end-to-end virtual representation of the microgrid
which can be efficiently deployed to scale the system configurations, test different power supply
and load scenarios, and fine-tune system performance. This lays a solid foundation for physical
prototypes, saving time and fostering optimal resource allocation during implementation.Includes bibliographical reference
Feasibility study on hydrothermal carbonization of shrimp shell waste: emphasis on hydrochar characterization and chitin retention
No full textThe Canadian shrimp processing industry generates substantial quantities of shell waste
rich in chitin—a valuable biopolymer with broad applications, from biomedicine to environmental
remediation. However, the high moisture content and rapid degradation of shrimp shell waste
present challenges for efficient chitin extraction. This thesis investigates hydrothermal
carbonization (HTC) as a sustainable pre-treatment method to stabilize shrimp shell biomass,
enhance chitin isolation, and produce a versatile carbon-rich hydrochar by-product. HTC, effective
for processing high-moisture biomass, offers an energy-efficient alternative to conventional drying
and chemical treatments (e.g., hydrochloric acid and sodium hydroxide), providing a scalable
solution for sustainable waste management.
In this study, the effects of varying HTC conditions—including temperature, residence time,
and water-to-biomass ratios—on shrimp shell hydrochar yield and characteristics were
systematically examined. Detailed analyses, including surface area, ash content, pH, mineral
composition, and functional group identification via FTIR, were conducted to assess the potential
of HTC-treated hydrochar as an intermediate product for chitin extraction. Results indicate that
optimized HTC conditions reduce organic impurities while retaining key structural properties of
chitin, effectively streamlining its isolation. Furthermore, the residual hydrochar exhibits
properties suitable for environmental applications, including potential uses as a bioadsorbent and
soil amendment.
This work offers a dual-benefit approach for the seafood industry, addressing waste
stabilization and enhancing chitin recovery through HTC pre-treatment. Future research should
focus on refining HTC parameters to maximize chitin purity and yield, investigating additional
post-HTC purification steps, and exploring the functional performance of HTC-derived hydrochar
in specific environmental applications, such as heavy metal adsorption and soil nutrient
enhancement. These efforts will contribute to establishing a more comprehensive and sustainable
waste valorization pathway, advancing circular economy principles within the seafood industry.Includes bibliographical reference
Dynamic models for fish stock productivity: state-space hidden Markov models and mixture models
No full textHidden Markov models (HMMs) and state-space models (SSMs) are complementary
methodologies for capturing discrete (regime-like) and continuous variations, respectively,
in the sense that HMMs typically use separate parameter sets for each regime,
whereas SSM parameters evolve continuously and are often correlated over time. In this
work, we combine the strengths of both approaches by developing HMMs with serial
correlation and implementing them efficiently. Resolving recruitment productivity
changes is crucial to effective fisheries management as shifts in the stock-recruitment
(SR) relationship redefines levels of sustainable removals. To account for interactions
between SR parameters and other components of stock assessment models, we embed
hidden Markov SR models within the broader stock assessment framework. Additionally,
we incorporate covariates into the transition probabilities of the HMM to
address nonstationarity and substantially reduce model complexity. Simulation and
case studies demonstrate the strong performance of this novel methodology.
This study also investigates temporal changes in the maturation dynamics of American
plaice using three modeling approaches: an SSM, an HMM, and an additive logistic
mixture model (ALMM). Fisheries management is usually focused on maintaining
the mature component of a stock at a level expected to maximize egg production
and future stock productivity. The mature stock is typically measured using the
spawning stock size, which depends on the proportion mature-at-age or length (i.e.,
maturity). Many stocks in the Newfoundland and Labrador region have experienced
large changes in maturity over time. The SSM captures strong temporal dependence
and gradual shifts in the age at 50% maturity. The HMM identifies eight discrete
regimes representing abrupt changes in maturation parameters, while the ALMM,
with five regimes, provides the best fit, capturing distinct maturation patterns across
regimes. Collectively, these models reveal both continuous and regime-like changes in maturation, offering valuable insights into life-history variability and its implications
for population dynamics