identifier: Darwish, Ahmed Mohamed Diaaeldeen Ahmed ORCID: https://orcid.org/0000-0002-4681-7628 <https://orcid.org/0000-0002-4681-7628>  (2022) In vitro investigation of the flow dynamic characteristics downstream of a dysfunctional bileaflet mechanical aortic valve.  PhD thesis, Concordia University.

abstract:
Mechanical heart valve replacement is the preferred alternative in younger patients with severe symptomatic aortic valve disease. However, a series of complications represented in thrombus and
pannus formation are associated with the bileaflet mechanical heart valves. This leads to risks of valve leaflet dysfunction (i.e., obstruction), which can be a life-threatening event. Therefore, there is an urge for a rapid and accurate diagnostic of the valve dysfunction. As a golden standard for valve function assessment, echocardiography may fail to assess the valve functionality. This leads to using another imaging modality such as computed tomography where the patient can be
exposed to X-ray radiations multiple times during the course of diagnosis and treatment. Thus, another radiation-free diagnostic tool is highly demanded in practice. This study explores a group of flow-based diagnostic parameters for five different scenarios of dysfunctional mechanical aortic valve that can be encountered clinically. Introducing such parameters comes in parallel with the recent access to obtaining cardiovascular flow fields clinically via techniques such as 4D-magnetic
resonance imaging or echocardiography- particle image velocimetry. Using an in vitro setup, physiological flow parameters have been obtained in a silicone model of the ascending aorta where
an actual bileaflet mechanical valve is placed. The instantaneous velocity field is obtained using particle image velocimetry while a blood analogue has been used as the working fluid. By analysing the normalized axial velocity profiles downstream the valve, a clear discrimination between all dysfunctional cases can be reached. Moreover, the effect of the induced  flow disturbance by the
valve dysfunction is quantified on various critical parameters such as the viscous energy dissipation, the wall-shear stress and the accumulated viscous shear stresses on passively advected particles.
These parameters can provide a clear insight into the progression of valve obstruction, in other words, a slight valve obstruction may lead to a complete blockage. This thesis also explores the application of modal decomposition in order to deduce the flow coherent features associated with each dysfunctional scenario. The results show the ability of proper orthogonal decomposition derived metrics to differentiate between healthy and dysfunctional cases. Moreover, reduced-order
modeling has been thoroughly investigated not only for the velocity field but also for higher order flow characteristics. Through the reduced-order models, a significant reduction on the original size of the velocity fields can be reached. Such application can gain more interest in managing
the storage of such data. Another axis of the analysis focuses on the Lagrangian perspective of fluid transport which can be an essential tool to understand the effect of valve dysfunction on the blood transport inside the ascending aorta. Under this analysis, the particle residence time inside the ascending aorta is analyzed which can be used to identify the dysfunctional scenario being associated with higher blood stasis time. This analysis can suggest which scenario induces higher
risk complications such as clot formation. As the transport of blood is governed by the Lagrangian coherent structures (LCS), revealing them through a geometrical approach has, therefore, been reported here. Utilizing the extracted repelling and attracting LCS, a new technique for the evaluation of the highest accumulated shear stresses is applied along the Lagrangian trajectory of particles being released from these structures where the highest stretching occurs. Such novel
analysis targets specific locations in the flow that witness higher level of shear rate which can be generalized to evaluate the hemodynamic performance of newly developed heart assisting devices.
Furthermore, the induced non-laminar flow behavior by the valve dysfunction is analyzed using the time-frequency spectra of velocity signals at selected points in the ascending aorta. As the
revealed LCS via a geometrical approach identifies only the transport barriers in the flow (i.e., the barrier between flow regions with different dynamics), a more intuitive method to reveal the blood transport skeleton (i.e., the interior of the coherent structure) is required. Therefore, the final  axis of this thesis explores the application of Lagrangian trajectory graphs which can be combined
with a spectral clustering algorithm in order to detect the
ow coherent regions. The identified coherent sets have a large inner mixing between its members, while mixing between different sets
is minimized. The identified coherent sets have different distributions, sizes and numbers for each dysfunctional scenario. Moreover, the identified coherent sets enclose representative coherent
structures in the flow such as the vortical structures. Furthermore, classical measures of the constructed graph such as the nodal degree and clustering coeffcient provide more insight into the mixing and agglomeration between particles which is critical to understand the blood transport and to assess the potential of thrombus formation.


identifier: Kupis, Dorota  (2022) The Political Struggle Behind the Delgamuukw Case: The 1994-1996 Trilateral Treaty Negotiations with the Gitxsan and Wet’suwet’en.  Masters thesis, Concordia University.

type: Thesis NonPeerReviewed

abstract:
This thesis examines the political struggle behind the Delgamuukw court case, particularly the 1994-1996 trilateral treaty negotiations with the Gitxsan and Wet’suwet’en.
The Gitxsan and Wet’suwet’en’s quests to have their Aboriginal rights and title recognized, and to prevent resource depletion in their hereditary territories, were intricately connected and multi-faceted. The Delgamuukw court case, which is often treated as a distinct issue, should be examined in the context of all significant events, both those which took place in the Gitxsan and Wet’suwet’en territories, as well as those at the negotiating tables. Although Aboriginal peoples’ struggle to preserve their cultural identity dates back to their early contact with the newcomers, colonial governance changed significantly in the 1980s. The neo-liberal governments of Canada and British Columbia moved from the paternalistic policies of the Indian Act to supporting industrial encroachment on a large scale. Neo-liberal governments tend to show benevolence. In fact, their policies may be as harmful as the colonial policies from the first half of the 20th century. In 1990, British Columbia joined the treaty negotiations and commissioned the establishment of the B.C. treaty negotiations process. The Gitxsan and Wet’suwet’en were among those First Nations who undertook negotiations with the provincial government soon after the process had been established. Therefore, their experience provides valuable insight into how this new process started in the 1990s. Since that time, the B.C. treaty process has been extremely unproductive, and the Gitxsan and Wet’suwet’en trilateral treaty negotiations are among the many examples of its failure.


identifier: Sadiki, Abdeladim  (2022) Deep Reinforcement Learning For The Computation Offloading In MIMO-based Edge Computing.  Masters thesis, Concordia University.

abstract: Multi-access Edge Computing (MEC) has recently emerged as a potential technology to serve the needs of mobile devices (MDs) in 5G and 6G cellular networks. By offloading tasks to high-performance servers installed at the edge of the wireless networks, resource-limited MDs can cope with the proliferation of the recent computationally-intensive applications. In this thesis, we study the computation offloading problem in a massive multiple-input multiple-output (MIMO)-based MEC system where the base stations are equipped with a large number of antennas. Our objective is to minimize the power consumption and offloading delay at the MDs under the stochastic system environment. To this end, we introduce a new formulation of the problem as a Markov Decision Process (MDP) and propose two Deep Reinforcement Learning (DRL) algorithms to learn the optimal offloading policy without any prior knowledge of the environment dynamics. First, a Deep Q-Network (DQN)-based algorithm to solve the curse of the state space explosion is defined. Then, a more general Proximal Policy Optimization (PPO)-based algorithm to solve the problem of discrete action space is introduced. Simulation results show that our DRL-based solutions outperform the state-of-the-art algorithms. Moreover, our PPO algorithm exhibits stable performance and efficient offloading results compared to the benchmarks DQN and Double DQN (DDQN) strategies.


identifier: Eghtedari, Sepideh  (2022) Digital Art History: Moving Towards a Decolonizing Methodology.  Masters thesis, Concordia University.

abstract: This thesis examines current approaches to digital art history, while arguing for the importance of integrating decolonizing methodologies into digital platforms. As a case-study, the thesis analyzes how the artwork of Nadia Myre (an Algonquin member of the Kitigan Zibi Anishinabeg First Nation, b. 1974) appears on the websites of the Montreal Museum of Fine Arts, Art Mûr gallery and AbTeC virtual gallery. In this thesis, I draw on the visual theorist Johanna Drucker’s distinction between “digitized art history” and “digital art history,” as well as concerns raised by the art historian Nuria Rodríguez-Ortega about the techno-determinism surrounding digital art history – to construct a critical approach to the process of art history going digital. I offer decolonizing methodology as a way forward that implicitly answers these scholars’ calls for methodological complexity in digital art history. Referring to Linda Tuhiwai Smith’s influential writings on decolonizing methodologies, I use the concepts of “remembering” and “reframing” as decolonizing sub-categories, or strategies, as a theoretical framework through which to examine a range of digital platforms. Even though these sub-categories are not the only possible approaches to take, they are a compelling place to start investigating how digital art history resonates with older art historical methodologies, and how digital practices can transform art history in a critical way.


identifier: Nasfi, Rim  (2022) Modeling Semi-Bounded Support Data using Non-Gaussian Hidden Markov Models with Applications.  PhD thesis, Concordia University.

abstract: With the exponential growth of data in all formats, and data categorization rapidly becoming one of the most essential components of data analysis, it is crucial to research and identify hidden patterns in order to extract valuable information that promotes accurate and solid decision making. Because data modeling is the first stage in accomplishing any of these tasks, its accuracy and consistency are critical for later development of a complete data processing framework. Furthermore, an appropriate distribution selection that corresponds to the nature of the data is a particularly interesting subject of research. Hidden Markov Models (HMMs) are some of the most impressively powerful probabilistic models, which have recently made a big resurgence in the machine learning industry, despite having been recognized for decades. Their ever-increasing application in a variety of critical practical settings to model varied and heterogeneous data (image, video, audio, time series, etc.) is the subject of countless extensions. Equally prevalent, finite mixture models are a potent tool for modeling heterogeneous data of various natures. The over-use of Gaussian mixture models for data modeling in the literature is one of the main driving forces for this thesis. This work focuses on modeling positive vectors, which naturally occur in a variety of real-life applications, by proposing novel HMMs extensions using the Inverted Dirichlet, the Generalized Inverted Dirichlet and the BetaLiouville mixture models as emission probabilities. These extensions are motivated by the proven capacity of these mixtures to deal with positive vectors and overcome mixture models’ impotence to account for any ordering or temporal limitations relative to the information. We utilize the aforementioned distributions to derive several theoretical approaches for learning and deploying Hidden Markov Modelsinreal-world settings. Further, we study online learning of parameters and explore the integration of a feature selection methodology. Extensive experimentation on highly challenging applications ranging from image categorization, video categorization, indoor occupancy estimation and Natural Language Processing, reveals scenarios in which such models are appropriate to apply, and proves their effectiveness compared to the extensively used Gaussian-based models.


identifier: Al-Yawer, Faisal  (2022) Auditory-cognitive Associations in Older Adults: Differential Effects of Sex, Test Modality, and Hearing Measures.  PhD thesis, Concordia University.

abstract:
Auditory-cognitive associations in older adults: Differential effects of sex, test modality, and hearing measures

Faisal Al-Yawer, Ph.D.
Concordia University, 2022

This dissertation presents findings that address auditory-cognitive associations in older adults with hearing loss (HL), particularly with regards to sex-related differences in said associations.
Manuscript I (Chapter 2) reports the psychometric properties of the Montreal Cognitive Assessment scale (MoCA) when hearing-related items are excluded from scoring (MoCAModified). This involved a cross-sectional analysis of the original MoCA validation study data in healthy older adults, older adults with mild cognitive impairment (MCI), and older adults with mild Alzheimer’s disease (AD). Our findings showed that, compared to the original MoCA, MCI sensitivity was substantially reduced when all auditory subtests were omitted, with the biggest contribution to the reduction coming from the delayed recall subtest. This Chapter highlights the
contribution that hearing-dependent subtests have on the accuracy of the MoCA.
Manuscript II (Chapter 3) examines sex-related differences in the associations between MoCA scores and pure-tone average (PTA) in healthy older adults. MoCA-Modified scores were also
calculated for all participants to assess the contribution of hearing-dependent items. Results showed that women with normal hearing were more likely to pass the MoCA compared to their counterparts with HL. In contrast, no associations were observed in men. Regression analysis showed an interaction between sex and PTA in the worse ear. PTAs were significantly correlated with both MoCA and MoCA-Modified scores in women, but not in men. This suggests significant sex-related differences in auditory-cognitive associations even when hearing-related test items are omitted.
Manuscript III (Chapter 4) examines sex-related differences in auditory-cognitive associations in a sample of individuals with MCI. In this cross-sectional analysis, we examined sex-related
differences in hearing, as measured by both PTA and the Canadian Digit Triplet Test (CDTT), and cognition, as measured by the MoCA, Rey Auditory Verbal Learning (RAVLT), and the
Brief Visuospatial memory test (BVMT-R). Women with better hearing on either measure outperformed their worse hearing counterparts on the MoCA. Women with normal hearing
showed correlations between CDTT SRTs and MoCA and RAVLT scores. Men but not women showed an effect of hearing on the BVMT-R. Generally, this dissertation points to the existence of sex-related differences in auditory-cognitive associations and discusses potential mechanisms that underly these observations, including the common cause and information degradation hypotheses.


identifier: Salim, Ibrahim  (2022) Pediatric Bone Age Analysis and Brain Disease Prediction for Computer-Aided Diagnosis.  PhD thesis, Concordia University.

abstract:
Recent advances in 3D scanning technology have led to a widespread use of 3D shapes in a multitude
of fields, including computer vision and medical imaging. These shapes are, however, often
contaminated by noise, which needs to be removed or attenuated in order to ensure high-quality
3D shapes for subsequent use in downstream tasks. On the other hand, the availability of largescale
pediatric hand radiographs and brain imaging benchmarks has sparked a surge of interest
in designing efficient techniques for bone age assessment and brain disease prediction, which are
fundamental problems in computer-aided diagnosis. Bone age is an effective metric for assessing
the skeletal and biological maturity of children, while understanding how the brain develops is
crucial for designing prediction models for the classification of brain disorders.
In this thesis, we present a feature-preserving framework for carpal bone surface denoising in the
graph signal processing setting. The proposed denoising framework is formulated as a constrained
optimization problem with an objective function comprised of a fidelity term specified by a noise
model and a regularization term associated with data prior. We show through experimental results
that our approach can remove noise effectively while preserving the nonlinear features of surfaces,
such as curved surface regions and fine details. Moreover, recovering high quality surfaces from
noisy carpal bone surfaces is of paramount importance to the diagnosis of wrist pathologies, such
as arthritis and carpal tunnel syndrome. We also introduce a deep learning approach to pediatric
bone age assessment using instance segmentation and ridge regression. This approach is comprised
of two intertwined stages. In the first stage, we employ an image annotation and instance
segmentation model to extract and separate different regions of interests in an image. In the second
stage, we leverage the power of transfer learning by designing a deep neural network with
a ridge regression output layer. For the classification of brain disorders, we propose an aggregator
normalization graph convolutional network by exploiting aggregation in graph sampling, skip
connections and identity mapping. We also integrate both imaging and non-imaging features into
the graph nodes and edges, respectively, with the aim of augmenting predictive capabilities. We
validate our proposed approaches through extensive experiments on various benchmark datasets,
demonstrating competitive performance in comparison with strong baseline methods.


identifier: Ogoms, Michael  (2022) Academic Performance in the 21st Century – Impact of Learning Disabilities.  Masters thesis, Concordia University.

abstract:
Research on students with learning disabilities in higher education tends to emphasize their
challenges and lower performance, which increases the stigma around this type of disability and
its role for individuals and organizations. The goal of this study was to promote a more
constructive view of what learning disabilities can provide to individuals and organizations by
investigating not only the negatives, but also the potential benefits of learning disabilities and
how certain contexts can enhance these benefits or buffer some of their negative consequences.
Overall, this study sheds light on an under-researched topic by looking for new ways to help
individuals with learning disabilities succeed in higher education and beyond.


identifier: Molaei, Amir  (2022) Modeling and Indirect Force/Position Control of Slender Continuum Robots.  PhD thesis, Concordia University.

abstract: In this thesis, a novel semi-analytical method is proposed for the pseudo-rigid body (PRB) modeling of highly flexible slender continuum robots (CRs) with no constraint on the number of degrees of freedom of the PRB model. The proposed method has a simple formulation and high precision. Furthermore, it can describe initially-curved variable-length CRs having a variable stiffness along the length. The versatility of the method is investigated for the PRB modeling of the slender CRs, such as steerable catheters and concentric tubes. A new analytical formulation is also introduced for the Cartesian stiffness of the CRs using the proposed PRB model. The existing formulations for the Cartesian stiffness in the literature, such as enhanced stiffness and constant stiffness models, fail to properly describe CRs force/deflection behavior with large nonlinear deformation. However, it is shown that the proposed method gives a high precision estimation of the applied force at the CR tip. Additionally, the proposed Cartesian stiffness is a function of deflection and allows indirect force estimation using the knowledge of only the tip point deflection, which makes it ideal for concentric tube robots (CTR) in vitreoretinal surgeries. The formulation of the stiffness is then used for the simultaneous force/position control of the CTRs interacting with a soft environment. The governing equation is a boundary value problem, and the existing control architectures for the simultaneous force/position control in rigid robotics cannot be directly used. Furthermore, in CTRs, the distributed friction force among the tubes and also at the entry port in vitreoretinal surgeries is beyond the desired force at the robot tip. Thus, the conventional method to map the task space forces to that of the joint space, which is fundamental in the existing force control methods, cannot be used.  Therefore, a new control architecture is devised for the indirect hybrid force/position control of a variable-length initially-curved CTR. The proposed method uses displacement as the control input to the robot and proves effective for environments with a wide range of stiffness.


identifier: Bernard-Brind'Amour, Marie  (2022) “Make way for magic!” Continuities and changes in the portrayal of the Refus Global manifesto.  Masters thesis, Concordia University.

abstract: In 1948, the Automatist artist group published the Refus Global manifesto, demanding liberation from Québec’s post-war conservatism. This thesis employs a critical cultural studies approach to trace the continuities and changes from 1948 to 1970 in the Refus Global’s portrayal as a site of affirmation and contestation of power by communities of interest, interpretation, and practice. The Refus Global is cast in an alternative media framework, and discourse analysis of archival research with frame analysis depicts its initial institutional repression. Next, this thesis contrasts these institutions’ adoption of the Refus Global in the wake of the Quiet Revolution with alternative media’s continued use of the manifesto as a tactic of resistance. An interview with journalist Françoise de Repentigny recounts her ties to the Automatist group and her firsthand experience of the era as a woman. This thesis concludes that the Refus Global’s portrayal as both a site of affirmation and contestation of power has ensured its longevity and legendary status in Québec today.


identifier: Grover, Hannah  (2022) From Fandom to Future Representation: Sapphic and Alternative Media as Creation.  Masters thesis, Concordia University.

abstract: For my research creation project, I wrote and produced a web series script and pilot centring 2SLGBTQIA+ Jewish women and their daily lives. I made an original narrative through the web series, as a device to explore fan production and subversion of the text Wicked. I did this by creat- ing my own “Fan” production— a script featuring positive representation of queer women in fan- dom, with the novel as a back drop and story catalyst, titled Mazel. The project was created in three stages: three interviews with members of the Canadian sapphic community pertaining to what they would like to see from sapphic representation, the completion of a script for a web se- ries written with inspiration from said interviews, and the filming of a short pilot webisode. I was then privileged to host a community talk-back in coordination with the Museum of Jewish Mont- real, wherein we discussed what sapphic folks considers good representation and negative repre- sentation. The project’s aim is to provide an invitation to fellow sapphic creators to explore how they want their stories told, on their own terms.


identifier: Hajari, Fahimeh  (2022) Balance Expertise, Workload and Turnover into Code Review Recommendation.  Masters thesis, Concordia University.

abstract:
Developer turnover is inevitable on software projects and leads to knowledge loss, a reduction
in productivity, and an increase in defects. Mitigation strategies to deal with turnover tend to disrupt and increase workloads for developers. In this work, we suggest that through code review
recommendation, we can distribute knowledge and mitigate turnover while more evenly distributing review workload. We conduct empirical investigations to understand the natural concentration
of review workload and the degree of knowledge spreading that is inherent in code review. Even
though the review workload is highly concentrated, with the top 20% of reviewers doing 80.19%
of reviews, code review naturally spreads knowledge and reduces the files at risk to turnover from
79.79% to 32.59%. To balance the review workload, reduce the Files at Risk to turnover, FaR,
and maintain high levels of Expertise during the review, we evaluate existing code review recommenders and develop novel recommenders. We find that prior work that assigns reviewers based
on file ownership concentrates knowledge on a small group of core developers, increasing the risk
of knowledge loss from turnover by up to 65.19%. Recent work, WhoDo, that considers developer workload, assigns developers that are not suffciently committed to the project and increases
FaR by 40.97%. We propose learning and retention aware review recommenders that when combined are effective at reducing the risk of turnover by -29.54%, but they unacceptably reduce the
overall expertise during reviews by -25.30%. Combining recommenders, we develop the SofaWL
recommender that suggests experts with low active review workload when none of the files under
review are hoarded by developers, but distribute knowledge when files are at risk to turnover. In this
way, we can simultaneously increase expertise during review with an ∆Expertise of 3.20%, reduce
workload concentration, ∆GiniWork by -12.00%, and reduce the fles at risk, ∆FaR, by -23.92%.
We then focus on the Risky File that have zero or one knowledgeable developers. We randomly
replace one of the actual reviewers with a suggested developer using TurnoverRec when we have a
risky file in the pull request. In this approach, we can increase Expertise substantially in comparison
to TurnoverRec and reduce FaR by -25.14%.
For the FaR++, we add a learner to the actual reviewers when we have a risky fle in the pull
request. We reduce FaR by -83.88% but increase the number of review by 13.14%. To reduce
the additional workload in AwareFaR, we only add reviewers when there are abandoned fles, this
decreases FaR by -37.51% and only increases the number of reviews by 34.24%.
Our data results and scripts are available in our replication package. 1


identifier: Blackburn, Jeanne  (2022) Embodying Water in the Anthropocene: Aquatic Immersion in the Work of Joan Jonas and Jacynthe Carrier.  Masters thesis, Concordia University.

abstract:
Responding to Etienne Turpin and Heather Davis’ argument that “art and aesthetics are central to thinking with and feeling through the Anthropocene,” this thesis examines the transformative possibilities of immersive, embodied, and sensory artistic practices in addressing environmental change. Two case studies – Moving off the Land (2016-ongoing) by American artist Joan Jonas (b. 1936) and brise glace soleil blanc (2016) by Quebec-based artist Jacynthe Carrier (b. 1982) – explore how art can enhance awareness of aquatic ecosystems and provide critical ways of engaging with endangered bodies of water. This
research project focuses on the artists’ commitment to water as a pressing environmental concern but also as a medium of embodiment and immersion that evokes alternatives to patriarchal, colonial, and capitalist relations to nature. Furthermore, the combination of performance, video, and photography in these two artworks is examined as a sensory strategy that amplifies perceptions of contemporary aquatic environments.


identifier: Sepehri, Parisa  (2022) Examining the Effects of Sadness and Anger Intensity and Variability on Stress and Health Symptoms in Old Age: The Role of Perceived Control.  Masters thesis, Concordia University.

abstract: This study examined whether the effects of sadness and anger intensity and variability on stress and health measures were moderated by between- and within-person differences of perceived control. It was expected that elevated and stable sadness would be associated with less stress and fewer health symptoms compared to anger. These associations were hypothesized to be more pronounced for older adults with generally low perceptions of control and who perceive lower-than-normal levels of control relative to older adults who generally perceive high or higher-than-normal levels of control, respectively. Community-dwelling older adults (n=178; 64- 98 years) completed a seven-day daily diary study. Each day, participants reported their most significant stressor, stressor-specific levels of sadness and anger, perceived levels of control, daily stress and health symptoms. Hierarchical linear modeling demonstrated main effects, linking sadness and, more strongly, anger intensity with elevated stress and health symptoms. The negative consequences of sadness intensity were dampened for participants with generally low, but not high, levels of control, but were amplified when adults faced less, compared to more, controllable stressors. The analyses further demonstrated a main effect of sadness variability, indicating that low, but not high, sadness variability predicted less stress. An interaction effect showed that anger variability predicted fewer health symptoms for adults with high control and high anger variability, exclusively. The results support the idea that discrete emotion intensity and variability have unique consequences on well-being and health, which are uniquely moderated by between- and within-person differences of perceived control.


identifier: Luo, Zhiwen  (2022) Extensions to Cross-collection Topic Models with Parallel Inference and Differential Privacy using Flexible Priors.  Masters thesis, Concordia University.

abstract:
Cross-collection topic models extend previous single-collection topic models such as Latent Dirichlet Allocation (LDA) to multiple collections. The purpose of cross-collection topic modelling is to model document-topic representations and reveal similarities between topics and differences among groups. The limitation of Dirichlet prior has impeded the state-of-the-art cross-collection topic models' performance, leading to the introduction of more flexible priors.

In this thesis, we first introduce a novel topic model, GPU-based cross-collection latent generalized Dirichlet allocation (ccLGDA), exploring the similarities and differences across multiple data collections by introducing generalized Dirichlet (GD) distribution to overcome the limitations of Dirichlet prior for conventional topic models while improving computational efficiency. As a more flexible prior, the generalized Dirichlet distribution provides a more general covariance structure and valuable properties, such as capturing collection relationships between latent topics and enhancing the cross-collection topic model. Indeed, this new GD-based model utilizes the Graphics Processing Unit to perform a parallel inference on a single machine, which provides a scalable and efficient training method for massive data. Therefore, the new approach, the GPU-based ccLGDA, proposes a scheme that incorporates a thorough generative process into a robust inference process with powerful computational techniques to compare multiple data collections and find interpretable topics. Its performance in comparative text mining and document classification shows its merits.

Furthermore, the restriction of Dirichlet prior and the significant privacy risk have hampered cross-collection topic models' performance and utility. The training of those cross-collection topic models may, in particular, leak sensitive information from the training dataset. To address the two issues mentioned above, we propose another novel model, cross-collection latent Beta-Liouville allocation (ccLBLA), which operates a more powerful prior, Beta-Liouville distribution with a more general covariance structure that brings a better capability in topic correlation analysis with fewer parameters than GD distribution. To provide privacy protection for the ccLBLA model, we leverage the inherent differential privacy guarantee of the Collapsed Gibbs Sampling (CGS) inference scheme and then propose a centralized privacy-preserving algorithm for the ccLBLA model (HDP-ccLBLA) that prevents inferring data from intermediate statistics during the CGS training process without sacrificing its utility. More crucially, our technique is the first to use the cross-collection topic model in image classification applications and investigate the cross-collection topic model's capabilities. The experimental results for comparative text mining and image classification will show the merits of our proposed approach.


identifier: Laporte, Marianne  (2022) Les principes de la Gestalt et des proportions dérivées du nombre d'or comme outils créatifs pour la conception d'environnements intérieurs.  Masters thesis, Concordia University.

abstract:
Cette recherche présente l’étude d'un procédé conceptuel pouvant potentiellement être utilisé lors de la réalisation d’un projet de design d’intérieur pour générer des impacts spatiaux efficaces via des gestes simples. Ce sont donc principalement les designers d'intérieur qui peuvent bénéficier de la lecture de ce travail, mais également les autres disciplines du design d'espace. La simplicité et l’épuration des formes sont considérées dans ce travail comme une avenue possible pour réduire les ressources financières et matérielles requises et ainsi répondre aux enjeux budgétaires et écologiques des projets. Ensuite, pour favoriser l’émergence d’un design efficace et de qualité, cette recherche met de l'avant des savoirs théoriques et étudie comment des possibilités conceptuelles peuvent émerger ce ceux-ci lorsque des principes issus de la Gestalt et des proportions sont transplantés dans la volumétrie d'un espace physique. C’est par l’entremise d’une revue de projets existants construits, d’investigations exploratoires volumétriques et de mises en application digitales qu’il a été possible d’avoir une vision plus éclairée de la potentialité des principes à l’étude à favoriser la mise en place d’interventions de design efficaces. L’étude permet de constater que les principes issus de la Gestalt ont le potentiel d'influencer la perception (cognition) spatiale de l'usager, de favoriser la mise en place d’un design visuellement distingué ainsi que de définir et de structurer les espaces. Ensuite, l’étude permet de constater que l'utilisation des principes de proportions inspirés du nombre d'or favorise un design esthétiquement harmonieux et adapté à la morphologie de l’homme ainsi qu’une symbiose avec la nature. L'harmonie des proportions favorise un bien-être à l'occupant du lieu. Finalement, l'utilisation d'un système de proportion peut agir à titre de guide structurel pour la conception de compositions spatiales.

Mots-clés : design d’intérieur, conception, spatialité, principes, Gestalt, proportion, nombre d’or, fonctionnalité, esthétisme, simplicité


identifier: Rayani, Marsa  (2022) Architectures and Algorithms for Content Delivery in Future Networks.  PhD thesis, Concordia University.

abstract:
Traditional Content Delivery Networks (CDNs) built with traditional Internet technology are
less and less able to cope with today’s tremendous content growth. Enhancing infrastructures
with storage and computation capabilities may help to remedy the situation. Information-Centric
Networks (ICNs), a proposed future Internet technology, unlike the current Internet, decouple
information from its sources and provide in-network storage. However, content delivery over in-network
storage-enabled networks still faces significant issues, such as the stability and accuracy
of estimated bitrate when using Dynamic Adaptive Streaming (DASH). Still Implementing new
infrastructures with in-network storage can lead to other challenges. For instance, the extensive
deployment of such networks will require a significant upgrade of the installed IP infrastructure.
Furthermore, network slicing enables services and applications with very different characteristics
to co-exist on the same network infrastructure.
Another challenge is that traditional architectures cannot meet future expectations for streaming
in terms of latency and network load when it comes to content, such as 360° videos and immersive
services. In-Network Computing (INC), also known as Computing in the Network (COIN), allows
the computation tasks to be distributed across the network instead of being computed on servers to
guarantee performance. INC is expected to provide lower latency, lower network traffic, and higher
throughput. Implementing infrastructures with in-network computing will help fulfill specific
requirements for streaming 360° video streaming in the future. Therefore, the delivery of 360° video and immersive services can benefit from INC.
This thesis elaborates and addresses the key architectural and algorithmic research challenges
related to content delivery in future networks. To tackle the first challenge, we propose algorithms
for solving the inaccuracy of rate estimation for future CDNs implementation with in-network
storage (a key feature of future networks). An algorithm for implementing in-network storage
in IP settings for CDNs is proposed for the second challenge. Finally, for the third challenge,
we propose an architecture for provisioning INC-enabled slices for 360° video streaming in next-generation
networks. We considered a P4-enabled Software-Defined network (SDN) as the physical
infrastructure and significantly reduced latency and traffic load for video streaming.


identifier: Duoduaah, Doreen  (2022) Pre-trained CNN and bi-directional LSTM for no-reference video quality assessment.  Masters thesis, Concordia University.

abstract: A challenge in objective no-reference video quality assessment (VQA) research is incorporating memory effects and long-term dependencies observed in subjective VQA studies. To address this challenge, we propose to use a stack of six bi-directional Long-Short Term Memory (LSTM) layers of different units to model temporal characteristics of video sequences. We feed this bi-directional LSTM network with spatial features extracted from video frames using pre-trained convolution neural network (CNN); we assess three pre-trained CNN, MobileNet, ResNet-50 and Inception-ResNet-V2, as feature extractors and select ResNet-50 since it showed the best performance. In this thesis, we assess the stability of our VQA method and conduct an ablation study to highlight the importance of the bi-directional LSTM layers. Furthermore, we compare the performance of the proposed method with state-of-the-art VQA methods on three publicly available datasets, KoNVid-1K, LIVE-Qualcomm, and CVD2014; these experiments, using same set of parameters, demonstrate that our method outperforms these VQA methods by a significant margin in terms of Spearman’s Rank-Order Correlation Coefficient (SROCC), Pearson’s Linear Correlation Coefficient (PLCC), and Root Mean Square Error (RMSE).


identifier: Baba, Fuad  (2022) Assessment and Mitigation of Overheating Risks in Archetype and Existing Canadian Buildings under Recent and Projected Future Climates.  PhD thesis, Concordia University.

abstract:
This research aims to develop a framework to assess and mitigate the overheating risks under projected future climates for both archetype and existing buildings.  More specific objectives are to 1) determine the contribution and correlation of individual building envelope parameters to the change in indoor temperature in conjunction with ventilation, therefore, to determine whether high-energy-efficient buildings required by Canadian building codes to reduce heating consumption in new buildings are at lower or greater overheating risk compared to old buildings; 2) develop an automated calibration procedure to calibrate a building simulation model based on the indoor hourly temperature to achieve high accuracy to be used overheating studies in existing buildings; 3) assess overheating risks under current and future extreme years and recommend effective mitigation measures; and 4) provide an optimal design for retrofitting existing buildings to achieve lowest heating energy demand and highest thermal and visual comfort in new building design. To achieve these objectives, a robust sensitivity-analysis (SA) and calibration method, a systematic framework for evaluating overheating and passive mitigation measures, and an optimization methodology are developed and applied to an archetype detached-house and existing-school-buildings.
The results showed that the archetype and existing Canadian buildings have experienced overheating under current climates and the overheating risks will increase dramatically under future climates. Due to the positive contribution of lower U-values of windows, walls, and roofs and SHGC, high-energy-efficient houses have a lower overheating risk than old buildings if adequate ventilation (>2.2-ACH) is provided. Natural ventilation in the high-energy-efficient house is sufficient to reduce the overheating risk under the recent climate but will require adding interior and exterior shading under future climates. For existing-school buildings, the calibrated model achieved high accuracy. The results also showed that the use of exterior blind roll or a combination of  night cooling and other mitigation measures that reduce solar heat gain is required under the recent climate and adding a cool roof will be required in future extreme years. For optimization design,  the applied optimization methodology can generate several optimal building design solutions based on Window-Wall-Ratio.


identifier: Guan, Jiajun  (2022) The impacts of different legal status of MFIs activities on economic development among developing countries.  Masters thesis, Concordia University.

abstract: This thesis investigates the impacts of for-profit and not-for-profit MFIs’ performance on economic development through a panel analysis between 2003 and 2018. The empirical results illustrate financial and social performances of for-profit and not-for-profit MFIs have their respective statistically significant influence on the host country’s poverty level and economic growth rate. However, due to the difference in corporate characteristics and strategic objectives between these two types of MFIs, the statistical and economic significance of the correlations against poverty or the growth index is not necessarily the same between the same performance metric of for-profit and that of not-for-profit MFIs. Furthermore, compared with the operating performances, consisting of financial and social performance, of not-for-profit MFIs, those of for-profit MFIs impose stronger impacts on real GDP growth, reflected in three transmission channels, including capital investment, export, and imports.……


identifier: Eslamioqani, Elnaz  (2022) Designing Playful Urban Installations: An Exploration of Participatory Methods.  Masters thesis, Concordia University.

abstract: For decades the human dimension has been neglected in urban planning topics. With the emergence of modernism, streets started to get larger in order to accommodate more cars, and step by step, the space for pedestrians has been reduced, dictated by the rhythm of the automobile flow. With the invasion of cars into cities, the high-rise buildings and towers made cities less and less pleasant for inhabitants. In return, city life studies demonstrate where conditions for pedestrians are improved, social and recreational activities increase extensively. In light of this situation, a number of cities have integrated playful urban installations to revitalize city centers.  In this research, the creative practice of designing four concepts of interactive urban installations through a research through design (RtD) approach combined with a reflective practice is described. Then since incorporating the notion of play in a way that encourages social interactions requires a good understanding of human behavior, site observations of two urban installations were also conducted in Montreal. Ultimately, recurring events and themes were investigated and turned into co-design activities for establishing participatory workshops. This process proved to be particularly useful for validating the developed concepts with potential users and created the ground for further reflection. Through this exploration, the core concepts of participatory practices were addressed which reconcile with the current endeavor for transforming situations to make cities more enjoyable and welcoming in the future.


identifier: Bouhamed, Omar ORCID: https://orcid.org/0000-0002-6595-5663 <https://orcid.org/0000-0002-6595-5663>  (2022) AI-Powered Time Series Forecasting Frameworks For Building Energy Management Systems.  Masters thesis, Concordia University.

abstract:
Energy, as an essential aspect of socioeconomic growth, has remained an intriguing issue for many researchers worldwide. The rising need for energy drives academics and researchers to develop novel solutions for improved energy utilization.
The main contribution of this thesis is two-fold. First, we introduce an occupancy prediction framework to improve the efficiency of energy management systems in smart buildings. Occupancy prediction heavily depends on historical occupancy-related data collected from various sensor sources. Unfortunately, a major problem in that context is the privacy constraints of collecting training data. This situation inspired us to rethink the occupancy prediction problem, proposing the use of an original principled approach based on occupancy estimation via interactive learning to collect the needed training data. Following that, the collected data, along with various features, was fed into several algorithms to predict future occupancy. This fold mainly proposes a weakly supervised occupancy prediction framework based on office sensor readings and occupancy estimations derived from an interactive learning approach. Two studies are the main emphasis of this part. The first is the prediction of three occupancy states, referred to as discrete states: absence, presence of one occupant, and presence of more than one occupant. The purpose of the second study is to anticipate the future number of occupants, i.e, continuous states. Extensive simulations were run to demonstrate the merits of the proposed prediction framework's performance and to validate the interactive learning-based approach's ability to contribute to the achievement of effective occupancy prediction.

Second, given that an accurate electric power load forecasting framework is critical for power utility companies as it increases control over the relevant infrastructure, resulting in significant improvements in energy management and scheduling, we propose an encoder-decoder model that takes advantage of the expressiveness of transformer-based encoders to produce probabilistic forecasts. Two real-world datasets are utilized to incorporate the performance of the proposed framework on two different types of data: hourly load data from the power supply company of the city of Johor in Malaysia and hourly load consumption data from one of Grenoble Institute of Technology's buildings. The former represents aggregated data, which makes identifying patterns and trends easier, but the latter was taken from a single building (non-aggregated), which increases the difficulty of forecasts. The model's performance is discussed across multiple time horizons, including 24-hour, 1-week, and 1-month predictions. The framework achieved notable improvements compared to the used baseline, Amazon DeepAr, where accuracy was improved from 87.2 percent to 96.2 percent for Malaysian data and from 52.3 percent to 68.2 percent for Grenoble data for 24 hours ahead forecasting, from 84.7 percent to 89.7 percent for Malaysian data, and from 45.5 percent to 57.2 percent for Grenoble data for 1 month ahead forecasting.


identifier: Politowski, Cristiano  (2022) Improving Video Game Balance Testing Using Autonomous Agents.  PhD thesis, Concordia University.

abstract: As the complexity and scope of game development increase,  playtesting (game testing) remains an essential activity to ensure the quality of video games. Yet, the manual, ad-hoc nature of game testing gives space for improvements in the process. In this thesis, we research, design, and implement an approach to enhance game testing to balance video games. Instead of manually testing games, we present an automated approach with autonomous agents to aid game developers to assess the game's balance. We describe the process of training the agents, playing the game, and assessing the game balance using game attributes. We validated our testing process with two platform games. We conclude that the use of autonomous agents to test games is faster than the manual feedback loop and provides a viable solution for game balancing, showing spikes in difficulty between game versions and issues with the game design.


identifier: Assoé, Steve  (2022) Exploring the Creation and Expansion of a Value Regime through the Nascent Technology of Non-Fungible Tokens.  Masters thesis, Concordia University.

abstract: How does a new technology become valuable? Existing literature proposes that an object is perceived as valuable due to structures involving the production, evaluation, distribution, and exchange of value. Such structures are termed “value regimes.” While existing work explains the transformation of value regimes or changes in the perceived value of an object as it moves between value regimes, we know less about how value regimes come to be and expand. This study answers this gap by exploring the expansion of the value regime of the nascent technology of non-fungible tokens (NFTs). To theorize the process through which a value regime expands, I collected and analyzed qualitative data composed of interviews, podcasts, newspapers, magazine articles, conferences, and webinars focusing on the NFT market. My analysis demonstrates that the three elements constituting a value regime (normative and cultural values, governance mechanisms, and economic models of value creation and distribution) expand from specific mechanisms that lead to a value regime’s growth. Normative and cultural values support expansion through the promotion of norms and values, the resolution of internal challenges, and challenges to the entry of market actors with misaligned values. Governance mechanisms support expansion through the entry of regulative bodies and the creation of standards. Economic models support expansion through the creation of new modes of value exchange, the creation of new methods of value creation and distribution, and the simplification of exchange mechanisms. Last, I provide potential limits to expansion and expand on the model’s implications for managers.


identifier: Shaw, David  (2022) Terrestrial Realism: Climate Fiction Beyond Liberal Humanism.  PhD thesis, Concordia University.

abstract:
The rise of the Anthropocene in the public imaginary has coincided with the emergence of a particular mode of realism in contemporary fiction that self-consciously struggles against its own tendency toward anthropocentrism. As this dissertation argues, this turn positions contemporary realism as a particularly generative literary mode for addressing the Anthropocene: This project builds on a conception of realism described by Fredric Jameson, for whom realism is a literary mode that emerges in the tension between narrative and immediate experience. Thus, if the present moment is one characterized by a kind of anxious preoccupation with the struggle to articulate the human’s newfound position as an agent of geological impact, then realism, in the Jamesonian sense, seems well situated as a site in which one could encounter alternative modes of articulating the human’s relationship to the rest of the planet. This contention is substantiated through an examination of the theoretical intersection of literary realism and the Anthropocene, followed by a series of close readings of novels in which this literary mode, which I’ve termed “terrestrial realism,” is generatively deployed. Ben Lerner’s 10:04 and Barbara Kingsolver’s Flight Behavior illustrate the problematics of comprehending climatological scale, Jenny Offill’s Weather and Thomas King’s The Back of the Turtle dramatize the uneven distribution of pressures exerted by environmental change, and Richard Powers’ The Overstory explores the possibility of kinship between humanity and nonhuman life. In each case, the terrestrial realism of these novels works to subvert the anthropocentric individualism that is so often seen as a
dominant characteristic of the realist novel and demonstrate realism’s utility in articulating a mode of fiction that can escape the anthropocentric constraints of liberal humanism and bring itself back down to earth.


identifier: Lathiff, Fathima Nihatha Abdul  (2022) Dependency Encoding for Relation Extraction.  Masters thesis, Concordia University.

abstract: The surge in information in the form of textual data demands automated systems to extract structured information from unstructured data. Relation extraction plays a key role in the process, with the aim of extracting semantic relations between entities in a text. Since dependency parse trees are capable of capturing the grammatical structure of sentences, this thesis experiments with different encodings of the dependency parse tree to distinguish different semantic relationships. Experiments are conducted on three different data sets that vary in domain and complexity and experimented with varying encoding schemas that can be grouped into two. The first group focuses on encoding the structure of the dependency parse tree with a Deep Graph Convolution Neural Network (DGCNN). The second group focuses on encoding the linguistic features obtained from the dependency parse tree with classical machine learning models such as Random Forest, Support Vector Machine, and Feed-Forward Network, and deep models such as BERT and Transformer encoder stack. The objective of this thesis is not to achieve state-of-the-art (SOTA) performance, rather to evaluate how dependency parse tree based linguistic features perform on different encoding schemas, including deep transformer-based models, on the relation extraction task. The results of the experiments show that these features on certain data sets being less computationally demanding are competitive for complex language models such as BERT, and incorporating them externally to BERT improves the performance rather than confounding.


identifier: Ozugergin, Imge ORCID: https://orcid.org/0000-0001-8667-4943 <https://orcid.org/0000-0001-8667-4943>  (2022) Diversity in cytokinesis and the regulation of cytokinesis across cell types.  PhD thesis, Concordia University.

abstract: Cytokinesis physically cleaves a cell into two through the assembly and constriction of an actomyosin ring. This process is crucial for growth and development, and the core machinery is highly conserved across metazoans. Studies in different systems have shown that both spindle-dependent and -independent mechanisms control this machinery. However, these mechanisms appear to vary widely among organisms and cell types. In addition, most of our knowledge of cytokinesis has been generated using only a couple of transformed cell types cultured in vitro, or in early embryos before cells adopt fates. This raises the question of how cytokinesis is regulated in diverse cell types and developmental contexts. This thesis characterizes cytokinesis in cells with different fates in C. elegans, and in mammalian cultured cell lines that have not been studied in this context before. In Chapter 2, we provide the first in-depth description of cytokinesis in AB and P1 cells with different fates in the two-cell C. elegans embryo. We found that each cell type has unique cytokinesis kinetics, driven by different thresholds of myosin. Our results revealed that cell fate, size and/or ploidy are contributing factors that regulate myosin levels and/or organization to influence these kinetics. We also demonstrated how a chromatin-dependent mechanism regulates cytokinesis differently in the two cell types. In Chapter 3, we compare cytokinesis kinetics for the first time in 5 different cultured mammalian cell types by studying the localization of endogenously tagged machinery. We found that this machinery has distinct spatiotemporal localization which reflects differences in cytokinesis kinetics among the cell types. Overall, this thesis highlights the diversity in cytokinesis and cytokinesis regulation, and explores the criteria that should be considered when conducting or interpreting cytokinesis research.


identifier: Gong, Kirsten  (2022) Emotion reactivity in chronic primary insomnia: Neural correlates and relationship with responses to cognitive-behavioural therapy for insomnia.  Masters thesis, Concordia University.

abstract: Individuals with chronic insomnia have trouble falling or staying asleep, wake up earlier than desired, and have daytime complaints. Some individuals also have difficulty regulating their emotions, especially in response to sleep-related stimuli. Cognitive-behavioural therapy for insomnia (CBTi), the gold-standard treatment for insomnia, has been shown to improve sleep. But, it is still unclear if CBTi impacts the neural activations underlying emotional reactivity in adults with insomnia and if emotion reactivity plays a role in CBTi treatment response. Thus, the first aim of this study was to investigate brain activity, using functional magnetic resonance imaging, during an emotion reactivity task in adults with insomnia and healthy sleepers. Secondly, we examined the effects of CBTi on brain activity during this emotion task in adults with insomnia. Lastly, we determined if brain activity at baseline was predictive of CBTi treatment response. While no differences in brain activity in response to sleep relative to neutral images were found between adults with insomnia and healthy sleepers at baseline, different patterns of activation in response to negative relative to neutral images were observed. Furthermore, after CBTi, adults with insomnia had reduced activity within the left insula and superior temporal gyrus in response to sleep relative to neutral images. But, there were no changes in affect. Lastly, brain activity in response to sleep relative to neutral images at baseline did not predict improvements in sleep. Overall, these findings contribute to the growing literature about sleep and emotions in adults with insomnia.


identifier: de Aguiar Lopes, Alan ORCID: https://orcid.org/0000-0003-3805-797X <https://orcid.org/0000-0003-3805-797X>  (2021) Maturation of heme antioxidant enzymes and their response to miconazole in Saccharomyces cerevisiae.  PhD thesis, Concordia University.

abstract:
Intracellular heme trafficking is important for cell respiration, antioxidant defence, and ergosterol biosynthesis in yeast, but information about this process is lacking. In Saccharomyces cerevisiae, heme production ends up with FeII insertion in protoporphyrin IX by ferrochelatase (FECH) but no heme acceptors from FECH have been identified. Mitochondrial cytochrome c peroxidase (Ccp1) is such a candidate due to its heme-independent synthesis and reported involvement in heme trafficking. However, FECH and Ccp1 are separated by the inner mitochondrial membrane, so this thesis examines Pet9, a well-characterized ADP/ATP transporter and a putative heme carrier, as a candidate to deliver heme from FECH to Ccp1. In Chapter 2, potential tools for this study were characterized including hem15Δ S. cerevisiae cells, which were shown to be devoid of FECH activity. Commercial cells homologously expressing N-terminally GST-tagged proteins also were examined to probe their applicability for GST pull-down assays, but cleavage of the fusion proteins negates their use. Chapter 3 reports on the LC-MS/MS analysis of GST pull-downs of soluble and membrane proteins from S. cerevisiae following the addition of exogenously expressed GST-apoCcp1 bait to different amounts of cell lysate. Screening the pull-downs at a 1:5 bait-prey ratio from lysates containing 0.6% N-octylglucoside identified 123 mitochondrial proteins as Ccp1-specific interactors, including FECH and Pet9. Computer modelling predicts that Ccp1-Pet9-FECH complexation is driven by electrostatic complementarity. Further computer modelling in Chapter 4 shows how Ccp1 maturation likely controls its association with Pet9 and hence heme channeling within the Ccp1-Pet9-FECH complex. More specifically, heme transfer from Pet9 to Ccp1 is possibly synchronized with the second cleavage of Ccp1’s mitochondrial targeting sequence. The outcomes of both Chapters 3 and 4 suggest that FECH, Pet9, and Ccp1 form a functional complex for heme transfer.
Heme is an essential coenzyme for the ergosterol pathway in S. cerevisiae. To probe links between heme and ergosterol biosynthesis, in Chapter 5 the S. cerevisiae proteome was analyzed by LC-MS/MS after cells were challenged with a sublethal dose of miconazole, a known Erg11 inhibitor. Proteins of 20 biochemical pathways were altered, including ergosterol and heme biosynthesis. Overall, this thesis supports a role for Ccp1 as a “frontline” protein in heme trafficking from FECH and sheds light on the importance of heme in the adaptive response of yeast to miconazole. The results suggest future investigations to clarify pathways and mechanisms of heme trafficking and how these, and heme production, could be targeted to potentiate antifungals.


identifier: Beaudin, Kayla  (2022) Testing the Bilingual Cognitive Advantage in Toddlers using the Early Executive Functions Questionnaire.  Masters thesis, Concordia University.

abstract: The present study aimed to assess differences in executive functioning between 39 monolingual and 42 multilingual 23-month-old toddlers, both when dichotomizing multilingualism and assessing it on a continuum. It was hypothesized that multilinguals, individuals with greater non-dominant language exposure, and individuals with more translation equivalents would perform better in the following domains: response inhibition, attentional flexibility, and regulation. No differences were expected for working memory. The Early Executive Functions Questionnaire, a newly developed parental report, was used to measure the four executive functions of interest. Multilinguals and individuals with greater non-dominant language exposure had significantly higher response inhibition; however, no differences were noted for any other executive function. Additionally, no associations between translation equivalents and executive functioning were found among French-English multilinguals (n = 31). Post-hoc analyses revealed that non-dominant language production had a positive correlation with working memory. The present findings support the notion of a domain-specific cognitive advantage for multilingual toddlers.


identifier: Esbati, Marjan  (2022) Assessment of greenhouse gas emissions from soybean cropping system: A case study of Ontario in Canada.  Masters thesis, Concordia University.

abstract: Soybean (Glycine max L.) is the fourth largest Canadian field crop covering around 2×106 hectares of land. Soybean crops take up more than 50% of Canada’s cultivated areas and contribute significantly to greenhouse gas (GHG) emissions in cropping system. The present study assesses GHG emissions from Ontario soybean fields. In this study, the crop districts of Ontario were divided into five categories: southern Ontario, western Ontario, central Ontario, eastern Ontario, and northern Ontario, and a general model for assessing emissions was developed. Emissions from the manufacturing and transportation of nitrogen/phosphorus (N/P) fertilizer, emissions from field operations, emissions from herbicide usage, and both direct and indirect emissions from agricultural lands were considered the major sources of GHGs. The results showed that total GHG emissions were around 7×105 Mg CO2-eq in 2018. The largest emission contributor was agricultural land, with emissions of 5.3×105 Mg CO2-eq, accounting for 77% of the total emissions. Moreover, GHG emissions were significantly influenced by environmental conditions. As precipitation/evapotranspiration (Pr/PE) decreased, total GHG emissions declined from southern Ontario to central Ontario. In southern Ontario (high Pr/PE), GHG emissions based on crop yield were 492 kg CO2-eq per hectare of seeding area, which was 46% greater than those in northern Ontario (low Pr/PE). GHG emissions from agricultural lands were the highest contributor to total GHG emissions among the four emission sources in all crop districts. Fertilizer N inputs accounted for the largest portion of agricultural land emissions in southern and central Ontario, while in other regions, crop residue N input was the largest source. A multivariate factorial analysis was also used to estimate the effect of uncertain parameters on system performance, and the main impacts, and their interactions were identified. The resutls demonstrated that farming practices had the most significant impact on total GHG emissions. Understanding the detailed impacts of these elements and their interactions can help determine major factors that influence total GHG emissions and allow us to implement appropriate strategies to mitigate agricultural GHG emissions.


identifier: Alam, Mohammad Jahidul  (2022) Multiple Drone and Truck Arc Routing Problem.  Masters thesis, Concordia University.

abstract: In this thesis we introduce the Multiple Drone and Truck Arc Routing Problem (MDTARP) which considers a fleet of drones used in synchronization with a ground vehicle to provide service to edges in a network within a given time-horizon. Drones launch from a ground vehicle to perform services on a set of edges and return to recharge batteries ready for its next trip. We formulate a multi-objective mathematical model that maximizes coverage of edges on a network based on given weights while minimizing unnecessary travel by drones and the ground vehicle. We develop an Iterated Local Search heuristic and a Cluster-based Location Search heuristic and assess their performance on several instances representing different scenarios. We compare results with solutions obtained using a commercial solver to showcase the effectiveness of the heuristics and perform computational experiments to provide recommendations for the users.


identifier: Therrien, Camille  (2022) Quebec Kindergarten Teachers' Perspectives on Play-Based Learning.  Masters thesis, Concordia University.

abstract:
With play recognized globally as a tool to promote children’s development and academic learning, the Quebec provincial government has given play a central role in their preschool
education program. However, kindergarten teachers are given little information on their roles during children’s play and teachers are left to determine how and the extent to which they should
integrate play in their classrooms. This study aims to gain a better understanding of Quebec kindergarten teachers’ beliefs about play-based learning, their roles during play, and their views
about Quebec’s mandated free play periods. Through case studies, four Quebec kindergarten teachers were interviewed and profiles were created. The profiles display the teachers’ perspectives of play and demonstrate how their beliefs affect their roles during the children’s play and their implementation of play in the classroom. Results reveal a lack of clarity amongst the teachers in defining play and play-based learning, and disagreements over the appropriate level of adult involvement - although the teachers all believe in taking on active roles during their students’ play. The profiles also reveal the teachers’ beliefs regarding the benefits of play and the issue of accountability required of kindergarten classrooms. Overall, the four kindergarten teachers interpret and present play very differently in their classrooms. The results
support the need for clearer and more consistent definitions of play-based learning and detailed information of the roles of adults during play, both in research and in the Quebec Educational
Program to enhance the practice of play and play-based pedagogies in kindergarten classrooms.


identifier: Viana de Medeiros, Tayline Paloma ORCID: https://orcid.org/0000-0001-7781-828X <https://orcid.org/0000-0001-7781-828X>  (2022) Carbon-Based Nanomaterials as Heterogeneous Catalysts for Biodiesel Synthesis.  PhD thesis, Concordia University.

abstract:
Energy demands are continuously rising, and currently, society remains dependent on fossil fuels as the primary energy source. The overconsumption of fossil fuels offers many drawbacks, including rising greenhouse gas emissions. Therefore, the search for more sustainable and renewable energy sources, such as biodiesel, has garnered significant interest. Commercially, biodiesel is produced using a homogeneous strong base catalyst (e.g. NaOH) through the transesterification of vegetable oils. While efficient, this process presents several limitations, such as the inability to recover and reuse the catalyst coupled with costly purification requirements.
Carbon-based nanomaterials have already been reported as efficient heterogeneous catalysts for biodiesel production. However, despite promising results, these materials usually require high temperatures and pressures to drive the reaction, increasing the energy requirements for the transesterification reaction and rendering large-scale use economically unfeasible. Polymeric carbon nitride-based structures (PCNs) and carbon dots (CDs) have emerged as promising candidates to overcome these limitations. PCNs and CDs are well-known for their low-cost synthesis and interesting optical properties, yet their role in driving chemically-catalyzed reactions remains relatively unexplored.
Herein, PCNs structures with different morphologies (nanosheets, fibers and dots) and amine-passivated CDs were synthesized and investigated as heterogeneous catalysts in the transesterification reaction of canola oil to biodiesel. In addition, the surface chemistry, morphology and physico-chemical properties of all materials were thoroughly characterized.
Bulk PCNs were synthesized and post-modified through acid and thermal treatments, whiled fibers were produced through a molten salt method. These different strategies give rise to materials with different morphologies, surface area and functional groups, allowing for understanding the effect of these parameters in their catalytic activity. It is demonstrated that surface chemistry is the most important aspect in designing more efficient PCN-based catalysts, as oxygenated functional groups are crucial to achieving high biodiesel yields.
Amine-passivated CDs (N-CDs) were chosen as a model system further to extend our knowledge of the role of surface chemistry in heterogeneous catalyzed transesterification reactions. By varying the type and concentration of the amine passivating agents, it was possible to control the degree of carboxylic acid to amine and amide functionalization. These results shed light on a plausible governing mechanism for the N-CD-catalyzed transesterification of canola oil to biodiesel, suggesting that both amines and carboxylic acids are active catalytic sites.
The transesterification reaction parameters were optimized, achieving >96% biodiesel conversion for both PCNs and N-CDs systems. The optimal conditions were achieved using  1  wt% catalyst loading for 3h in a solvothermal reactor at 150 °C and 100 °C for PCNs and N-CDs, respectively. In addition, the N-CDs were reused for at least five reaction cycles and demonstrated the system's ability to maintain high catalyst performance over several reaction cycles.
Lastly, we aimed to explore the knowledge acquired from the previous systems and reduce the energy requirements for biodiesel synthesis. We synthesized and thoroughly characterized polymeric carbon nitrides nanosheets (PCNNs) and dots (PCNDs) through a solid phase, low-temperature reaction. Their morphology and surface chemistry were tuned by varying the precursors’ ratio, and the materials were investigated as catalysts in the transesterification reaction of canola oil to biodiesel. Biodiesel conversion yields > 98% were achieved using a 5 wt% catalyst loading, oil to methanol ratio of 1:36 at 90 °C for 4 h, with the performance maintained over at least five reuse cycles. The reactions were carried out in a non-pressurized vial and at lower temperatures when compared to PCNs and N-CDs, reducing the energy requirements. In addition, kinetics studies were carried out to glean a deeper understanding of the catalytic mechanism, suggesting that the reaction mechanisms occur through a pseudo-first order mechanism.


identifier: Rossini, Bianca  (2022) Ultrasonography of the multifidus muscle in student circus artists with and without low back pain.  Masters thesis, Concordia University.

abstract:
Low back pain (LBP) is a major global health issue. Athletes and performing artists also suffer from LBP. Student circus artists’ daily training put constant stress on their spine and back. Proper back muscle function is critical for spinal stiffness and movement. Substantial research revealed structural and functional deficits of the lumbar multifidus muscle (LM) in patients with LBP. However, circus research remains scarce, and no data is available on the LM and LBP in this population. The purpose of this study was to explore the prevalence of LBP in student circus artists, investigate lumbar multifidus morphology and function in student circus artists with and without LBP and explore the relationship between LM asymmetry and LBP.

A total of 33 participants completed an online survey to acquire demographics, training history, brief injury history and LBP history. Thirty participants had body composition measurements and an ultrasound assessment of the LM at the 5th lumbar vertebrae. All examinations were performed at the participants’ respective circus school. Our primary measures included the assessment of LM morphology and function using ultrasound (manuscript 1). Our secondary measures included pain, training activity, catastrophizing, medical history in the past year and LBP-related disability assessed via a survey and questionnaires (manuscript 1 and 2).

This study explored the burden of LBP in student circus artists. Assessing LM characteristics using ultrasound may be a useful tool to identify artists’ injury risk and monitor changes following rehabilitation programs or throughout the school year leading to a more sustainable practice.


identifier: Ryan, Jacob  (2022) Worker Empowerment through Multi-Stakeholder Governance? A Solidarity Co-operative Case Study.  Masters thesis, Concordia University.

abstract: Multi-stakeholder co-operatives (MSCs), which allow for multiple parties (both consumer and worker, for example) to share in governance, have come to define a number of regional co-operative models worldwide and are often characterized as particularly inclusive and capable of expanding the democratic capacity of the co-operative movement. In Quebec, the solidarity cooperative—a multi-stakeholder model through which ownership is divided between multiple parties including workers, consumers, and “supporting members” who often represent other organizations —has proliferated significantly in the last several decades and directly encourages the formation of networks across the social economy through its unique governance structure. In addition to the strengths of this model, a number of challenges and tensions arise from its hybridization of worker and consumer co-operative models. This master's thesis examines these tensions from a worker’s perspective using a participant observation case study of The Hive Café, a solidarity cooperative operating out of Concordia University in downtown Montreal. Both formal and informal divisions between workers and other groups within solidarity cooperative governance are explored with the aim of extracting insights useful to those seeking to build socially-oriented economic alternatives.


identifier: Tavassoli Naini, Sina  (2022) Design, Modelling and Control of an Adaptive Vibration Isolator Featuring Magnetorheological Elastomer.  Masters thesis, Concordia University.

abstract:
Magnetorheological elastomers (MREs) are smart materials whose viscoelastic properties can be varied upon the application of an external magnetic field. They are solid analogue of well-known MR fluids (MRFs) in which magnetic particles are embedded in a non-magnetic elastomer matrix instead of carrier fluids. Compared with their fluid counterparts, MREs do not have problems associated with particles' sedimentation, stability and leakage often encountered in MRFs. Besides in contrast to MRF-based adaptive devices, MRE-based systems can provide field dependent variable stiffness and damping simultaneously due to viscoelastic properties of MREs. This unique behaviour of MREs enable them to be effectively utilized in the development of adaptive isolators or absorbers to supress vibrations in wide range of frequencies. The present research study aims to provide a comprehensive investigation of the material characterization and phenomenological modelling of MREs under varying dynamic loading conditions, design and development of a novel vibration and shock isolator featuring magnetorheological elastomers, design optimization of the proposed isolator to enhance its dynamic range and finally design and implementation of semi-active control strategies to mitigate vibration and shock under different external disturbances.
MREs with a 25% volume fraction of soft magnetic particles (carbonyl iron) were used to investigate variation of storage and loss moduli of MRE under varied frequencies, strain amplitudes, and magnetic field densities. Considering operation of MREs in the linear range, field dependent linear viscoelastic models based on the Kelvin–Voigt, Maxwell, Standard Linear Solid, and Generalized Maxwell models, were formulated to predict the variation of storage and loss moduli under varying driving frequency and applied magnetic flux densities. The performance of these models to capture the response behaviour of MREs under different applied frequencies and magnetic field were subsequently compared.
A semi-active MRE-based vibration isolator operating under shear mode with embedded electromagnet was then proposed. Analytical magneto-static model of the magnetic circuit of the proposed adaptive isolator was first formulated using Ampere’s law to estimate the induced magnetic flux density in the MRE region gaps versus applied current to the electromagnet. The validity of the analytical results was verified using the finite element magneto-static analysis. A multidisciplinary design optimization problem was subsequently formulated to optimize the isolator geometrical parameters as design variables to maximize its frequency bandwidth under weight, material magnetic saturation, and total volume constraints. A hybrid approach based on combination of Genetic Algorithm (GA) and gradient based Sequential Quadratic Programming (SQP) was used to accurately capture the global optimal solution for the optimization problem.
Finally, closed-loop control strategies, based on on-off sky-hook and PID, were implemented and compared to assess the capability of the proposed adaptive isolator to mitigate vibration and shock under different disturbances.


identifier: Syu, Jhan-Cyuan  (2022) Uniformization of Shimura Curves.  Masters thesis, Concordia University, University of Duisburg-Essen.

title: Uniformization of Shimura Curves

abstract:
A Shimura curve is a moduli scheme parametrize a certain family of abelian schemes.
After taking the formal completion, one can see that it is related to the formal scheme Omega hat
associated to the Drinfeld upper half plane. This is the well-known Cerednik-Drinfeld Theroem.
To prove this theorem, we need to develop a modular description of Omega hat via Deligne’s and
Drinfeld’s functor, and Cartier theory on formal modules is also used.


identifier: Gallant, Stephanie  (2022) Activity-Based Anorexia in Adult Rats: A Behavioural and Neurobiological Investigation of Resilience and Susceptibility.  PhD thesis, Concordia University.

abstract:
Anorexia nervosa (AN) is a life-threatening psychiatric illness characterized by severe caloric restriction, excessively low body weight, and extreme fear of weight gain. Up to 81% of individuals with AN exhibit high levels of physical activity which is associated with higher relapse, longer hospitalizations, and poorer outcomes. Mood and anxiety disorders, cognitive impairment, and alterations in reward processing are common in AN. Only about half of individuals with AN achieve full remission of symptoms and relapse is frequent. There is a pressing need for a better understanding of risk factors and underlying pathogenesis of AN. Activity-based anorexia (ABA) is an animal model of AN-like symptoms combining wheel access and food restriction resulting in increased running wheel activity, failure to increase food intake, and accelerated weight loss which can result in death if the animal is not removed from the experiment. While ABA has been used since the 1960s, only recently have researchers begun to explore the individual differences in response to ABA. The goal of this series was to establish the use of the model in our laboratory and to explore individual variability in ABA response by investigating behavioural and neurobiological differences between resilient and susceptible rats.
The experiments in Chapter 3 aimed to determine the ideal parameters to establish the use of the ABA model in our laboratory. ABA reliably developed in both male and female rats and female rats were particularly susceptible. Efforts to use behavioural measures of cognitive flexibility and anxiety- and depression-like behaviours during the ABA paradigm revealed that it is possible to do so without interfering with ABA development. In Chapter 4, we aimed to further characterize ABA susceptibility by assessing baseline anxiety- and depression-like behaviours, amphetamine-induced locomotor activity as an index of mesolimbic DA activity, and response to pharmacological treatment. In Chapter 5, we compared general neural activity between resilient and susceptible rats in several key brain areas using c-Fos immunohistochemistry. We followed up on these findings by assessing response inhibition, a facet of impulsivity that is dependent on prefrontal functioning. In Chapter 6, we examined the effect of ABA on later cocaine-taking behaviours and assessed for trait differences in response to cocaine. Overall, by comparing resilient and susceptible rats, we found important differences in baseline running wheel activity as well as in performance on the forced swim task. We also observed statistical trends for differences in neural activity in the prefrontal cortex and nucleus accumbens as well as differential responding to cocaine self-administration. These results highlight the importance of considering susceptibility to ABA to further our understanding of risk factors involved in the development, maintenance, and treatment response in AN.


identifier: Kremin, Lena van der Velde ORCID: https://orcid.org/0000-0002-4010-490X <https://orcid.org/0000-0002-4010-490X>  (2022) Untangling Bilingualism: Using Code-Switching to Understand Bilingual Language Development.  PhD thesis, Concordia University.

abstract:
Switching between two languages, or code-switching, is common in bilingual communities. However, little is known about the code-switching young bilinguals hear in their daily lives and how they process it. This dissertation investigated these two aspects of code-switching and proposed new models for defining bilingualism.
Bilingualism is difficult to define and model. In Chapter 2, I proposed that bilingualism researchers can integrate psychometric models, such as the factor mixture model and the grade-of-membership model, which incorporate both categorical and continuous properties. Such models can unify traditional approaches of defining bilingual groups with newer views of bilingualism as a continuous variable. These models will allow researchers to address a variety of research questions, advance theory, and lead to a deeper understanding of bilingualism.
In Chapter 3, I analyzed French–English parents’ code-switching in day-long at-home audio recordings, provided when their infant was 10 and 18 months old. Code-switching was relatively infrequent: an average of 7 times per hour (6 times/1,000 words) at 10 months, increasing to 28 times per hour (18 times/1,000 words) at 18 months. Parents code-switched more between sentences than within a sentence, and this pattern became more pronounced when infants were 18 months. Parents appeared to code-switch most frequently to bolster their infant’s understanding and teach vocabulary, suggesting that code-switching may support successful bilingual language development.
In Chapter 4, I investigated how bilingual children process code-switching, examining how 3-year-old bilinguals process sentences with code-switches at an uninformative determiner-adjective pair before the target noun (e.g., “Can you see el buen [sp. the good] duck?) compared to single-language sentences (e.g., “Can you see the good duck?”). Children were unexpectedly accurate at identifying the target noun in both sentence types, contrasting with previous findings that code-switching leads to processing difficulties. Surprisingly, exploratory results suggested that code-switching may have boosted comprehension for certain children.
In sum, this dissertation has illustrated how code-switching may support bilinguals’ language development. I discovered that parents code-switch to support their child’s learning and showed that children do not always have difficulty processing code-switching. Bilingualism is a multi-faceted phenomenon, and nuanced research is needed to capture this variability.


identifier: Howard, Ann-Louise ORCID: https://orcid.org/0000-0002-4063-0264 <https://orcid.org/0000-0002-4063-0264>  (2022) I Didn’t Know it was a Thing Either: Women Engineers’ Experience of Suffering in the Workplace.  PhD thesis, Concordia University.

abstract:
This Canadian study investigates women engineers’ lived experiences of suffering in the workplace and aims to contribute to addressing the persistent problem of attracting and retaining women in engineering. It is inspired by my own experience of suffering in the engineering workplace, which I inquire into deeply as part of this thesis in an autoethnographic study. The autoethnography plays an essential role of critical self-reflection in service of this thesis’ primary research. My research on women engineers’ experience of suffering in the workplace uses a phenomenological, reflective lifeworld approach (Dahlberg et al., 2008). This approach is not widely used in organizational studies because, I argue, it represents a radical paradigm shift that is not easily understood. I endeavor in this thesis to make it more accessible and illuminate its potential to create disruptive, productive knowledge.
For my primary research, I use a purposeful sampling procedure to identify six women engineers who, together, represent a rich variation of experiences of the phenomenon. Each participant provides a critical situation narrative in which they are asked to write a direct, personal account of “a meaningful and vivid memory of an incident in the workplace that contributed to your suffering.” They then participate in two in-depth conversational interviews where their experiences of severe and protracted distress are explored. Analysis of women engineers’ intimate, personal experiences of suffering in the workplace found that some women engineers who suffer are trapped in an oppressive, socially constructed reality in which they protect themselves from threats and sacrifice their dignity, self-worth, health, well-being, and job effectiveness. Analysis of my findings against existing research on women in engineering and microaggressions results in six provocative insights. Systemic interventions that acknowledge and address the inequality in engineering are proposed.


identifier: sanei, azin  (2022) The Impact of Urban Morphology and Construction Standards on the Energy Consumption of Neighborhoods.  Masters thesis, Concordia University.

abstract:
With the growing urban population, energy consumption and the CO2 emission of cities are constantly rising, and thus, it becomes important to address the cities' energy use. Multiple factors are important for urban scale energy consumption, mainly urban design and construction standards. Urban design and choice of morphology design are considered influential factors in urban scale energy consumption. This study tries to understand the impact of urban morphology and construction standards on urban scale heating and cooling demand by evaluating two case studies in two districts in Montreal, Canada. One of the case studies is in downtown Montreal; buildings have different height variations in this case study, while the second case study represents a neighborhood with uniform heights. Both case studies are different in density and surface-to-volume ratio. Previous studies have shown that morphological parameters significantly affect radiation received on external surfaces, affecting energy consumption. On the other side, building compactness, construction, and insulation standards are important factors in reducing energy consumption. To run the energy simulations, a software workflow was developed where the geometry of buildings is modified using Rhino and imported to grasshopper; the energy simulation for the buildings was completed using a combination of plugins of Ladybug tools which uses OpenStudio, EnergyPlus, and Radiance as backend engine.
To understand the effect of radiation on cooling and heating loads, two window locations are studied, showing 15% changes in heating loads when the windows are on one side of the buildings and 4% changes in heating loads when windows are located on both sides of the buildings in different orientations. Based on previous studies, two main morphological parameters are selected for a neighborhood to study. This study investigated the influence of orientation and surface-area-to-volume ratio (S/V represents changes in density and simplification in the model) for an as-build and multiple defined scenarios. Besides these morphological parameters, five different construction types using ASHRAE standards are selected, and heating and cooling demand are calculated for all the 330 models. Then the approximate solar potential for the models is calculated considering how much energy in all the models can be produced and covered by photovoltaic (PV) panels on roofs. Results indicate that even not ideal morphological design with very good insulation standards could produce 1.3 times more than the energy needed. In contrast, the best morphological model with a not insulated scenario will cover around 0.6 times the energy loads. The load calculation results show that the morphological parameters change the heating and cooling demand by a maximum of 45%. The results also show that when the insulation properties are modified to meet the statutory requirements of energy codes and even beyond the energy codes, a reduction of almost 80% in heating/cooling demand can be achieved. Thus, the results show that although morphological parameters are important in energy consumption and radiation received on surfaces, for example, if the surface-to-volume ratio changes significantly, the effects of construction standards are far more relevant for urban scale heating and cooling loads. To expand the conclusion, this study can be continued in the future by studying different case studies in different climate zones.


identifier: Shamshiri, Mohammad Amin  (2022) Classification of Breast Cancer Cytological Images using Transfer Learning and Deep Convolutional Neural Networks.  Masters thesis, Concordia University.

abstract: Microscopic analysis of breast cancer images is the primary task in diagnosing cancer malignancy, which requires high expertise and precision. Recent attempts to automate this highly subjective task have employed deep learning models whose success has depended on large volumes of data while acquiring annotated data in biomedical domains is time-consuming and may not always be feasible. A typical strategy to address this is to apply transfer learning using pre-trained models on a large natural image database (e.g., ImageNet) instead of training a model from scratch. This approach, however, has not been effective in several previous studies due to fundamental differences in patterns, size, and data features between natural and medical images. In this study, we propose and compare several transfer learning approaches that, in the pre-training phase, use both unrelated natural images and related histopathological images to our target data (i.e., cytological images) in order to classify breast cancer cytological biopsy specimens. To our best knowledge, this is the first reported effort to employ a histopathology data source in transfer learning to classify cytological images of breast cancer. Despite intrinsic differences between histopathological and cytological images, we demonstrate that the features learned by the deep networks during the pre-training are compatible with those obtained throughout fine-tuning with the target data set.  To thoroughly investigate this assertion, we explore three different strategies for training as well as two different approaches for fine-tuning deep learning models. The proposed method is compared with five state-of-the-art studies previously conducted on the same data set of cytological biopsy images, and we demonstrate that the proposed approach significantly outperforms all of them in terms of classification accuracy. Specifically, the proposed method boasts of improved classification accuracy by 6% to 17% compared to the state-of-the-art studies which were based on traditional machine learning techniques, and also enhanced accuracy by roughly 7% compared to those who utilized deep learning methods, eventually achieving 94.55% test set accuracy and 98.73% validation accuracy. Experimental results show that our approach, despite using a very small number of training images, has achieved performance comparable to that of experienced pathologists and has the potential to be applied in clinical settings.


identifier: Motaghi Moghadam, Zahra  (2022) Effect of the Acetylcholinesterase Inhibitor Donepezil on Human Immune Cells in Peripheral Blood Mononuclear Cells.  Masters thesis, Concordia University.

abstract: Donepezil is an acetylcholine esterase inhibitor that improves symptoms in Alzheimer’s Disease. It is known to stimulate cholinergic receptors on helper T cells and can change the pro and anti-inflammatory cytokines which is important in autoimmune diseases as well as neurodegenerative diseases. The effect of donepezil on modulating helper T cell differentiation the immune system is not clearly understood. To begin to address this question, peripheral blood mononuclear cells were studied from healthy participants' venous blood. The experiments were done using cell culture methods. The cytokines that were measured include anti-inflammatory IL-4, and pro-inflammatory IFNγ and IL-17A. Cell viability was determined with trypan blue after four days of incubation with activation, and different dosages of donepezil (0.8, 4, 20, and 100 ng/mL). Aggregate data illustrated the amount of IL-17A was lower after being treated with 20 ng/mL in comparison with 0.8 and 4 ng/mL. There was no significant change in the amount of IL-4, IFNγ, or cell viability after four days. In conclusion, T cells can be regulated by cholinergic drugs and receptors but the mechanism of action is not fully understood.


identifier: Navone, Giorgio  (2022) Hodge-Tate decomposition for p-adic abelian varieties with good reduction.  Masters thesis, Concordia University.

abstract:
The goal of this thesis project is to study the Cp-semilinear representation given by the p-Tate module of an abelian variety X over a local field K, following Fontaine’s paper “Formes différentielles et modules de Tate des variétés abéliennes sur les corps locaux”.
The main aim is to prove the Hodge-Tate decomposition for Tp(X)⊗Cp in terms of the Lie algebra of X and Xv. Thus, in the first chapter we compute the continuous cohomology groups of Cp(n) with respect to the absolute Galois group of K.
In the second chapter, Fontaine’s work analyse the module of Kähler differentials Ω of the extension  using an integration of invariant differentials along elements of the Tate module of a Zp-module Γ.
Finally, in the third chapter we prove Tate-Raynaud theorem using the identification Vp(Ω) = Cp(1) and then we derive the Hodge-Tate decomposition.