VictorJuiz/thesis huggingface dataset:
Development of a Technology-assisted Measurement of Limb Motion during Stepping within a Clinical Context
Keywords: Acquired brain injury
algorithm
BESTest
clinical assessment
event detection
Instrumentation

Instrumented measurement of limb motion during clinical assessments of balance may augment the capacity of current models of rehabilitation to optimize clinical outcomes. The aim of the present study is to develop, optimize and evaluate the accuracy of a novel, optical approach to measure limb motion during stepping tasks. This approach includes an optical sensor and an event detection algorithm. Algorithm development and optimization provided an average positive detection rate of 74%, a negative detection rate of 19.6% and an overall ICC of 0.77. The accuracy analysis results provided a good overall correlation (ICC=0.75), excellent (ICC>0.98) when detecting movement onset and offset, and poor (0.275) for movement duration. The agreement using Bland-Altman analysis shows a median overall bias of 212 ms and a 95% CI of 2.859s for the optical approach in relation to Vicon. In conclusion, the optical approach demonstrated potential for the detection of movement during stepping.
Investigating the Role of Histone Deacetylase 1 in the Pathogenesis of Atypical Teratoid/Rhabdoid Tumours
Keywords: Cancer
Genetics
Paediatric
Therapeutics

Atypical teratoid rhabdoid tumours (AT/RTs) are devastating embryonal brain tumours that usually develop before the age of two years, with a survivability of less than one year. They are characterized by loss of the SMARCB1 gene and high expression of histone deacetylase 1 (HDAC1). Genetic inhibition of Hdac1 led to varying results between replicates, such that no conclusions can be drawn at this time. Selective pharmacological inhibition of HDAC1 decreased cell number in Group 2 cell lines, with a concomitant increase in p21 protein expression. This suggests selective pharmacological inhibition of HDAC1 culminates in cell cycle arrest, but these results differ somewhat from those found following genetic inhibition. Future experiments will focus on generating stable cell lines expressing an inducible HDAC1 shRNA construct to further elucidate the role of HDAC1 in AT/RT pathogenesis.
HyScale: Hybrid Scaling of Dockerized Microservices Architectures
Keywords: autoscaling
cloud
Docker
microservices

Recently, microservices architectures have garnered the attention of many organizations--providing higher levels of scalability, availability, and fault isolation. Many organizations choose to host their microservices architectures in cloud data centres to offset costs. Incidentally, data centres become over-encumbered during peak usage hours and underutilized during off-peak hours. Traditional scaling methods perform either horizontal or vertical scaling exclusively. When used in combination, however, both offer complementary benefits and compensate for each other's deficiencies. To leverage the high availability of horizontal scaling and the fine-grained resource control of vertical scaling, two novel reactive hybrid autoscaling algorithms are presented and benchmarked against Google's popular Kubernetes horizontal algorithm. Results indicated up to 1.49x speedups in response times, 10 times fewer failed requests, and 35% increase in resource efficiencies. Moreover, a novel predictive approach is also explored using neural networks and a custom online learning technique indicating prediction errors as low as 3.77%.
Subway Station and Post-It Notes: The Kangnam Murder Case of 2016 and the Emergence of a New Form of Protest
Keywords: feminist movement
Space and memory

This thesis examines the Kangnam Murder Case of 2016 and how its participants used a street vigil as a site of protest against misogyny in South Korea. The thesis places the case within the changing contemporary socio-economic environment and contextualizes the vigil-turned-protests with the lineage of feminist movements from the 1920s to the 2000s. The Kangnam Murder Case’s vigil used the subway station as a site of memorialization and mobilization. Examining the use of post-it notes as a form of protest in the everyday space of a subway station illustrates the complex and contradictory ways that that voice may occupy space.
Investigation of Thin Film Polymeric Contaminants by Optical and Contact-Force Microscopy
Keywords: atomic force microscopy
infrared
phonon polaritons
polymer hydration

Here is investigated the presence of organic contamination on extremely flat surfaces of hexagonal boron nitride. Boron nitride has the ability to support phonon polaritons, which are strongly dependent on the material's dielectric properties. The effect of these thin films on polaritons is explored. It was found that the films were primarily comprised of poly-dimethyl siloxane type contaminants. Polymers are investigated through contact force AFM in order to understand mechanistic properties of micellular collections of polymer. Analysis through machine learning provides a promising means to mechanistic understanding of polymer clustering on surfaces.
The Use of Activity Monitoring and Machine Learning for the Functional Classification of Heart Failure
Keywords: ambulatory monitoring
clinical decision support
heart failure
NYHA (New York Heart Association)
steps
wrist worn devices

Background: Assessing the functional status of a heart failure patient is a highly subjective task. Objective: This thesis aimed to find an accessible, objective means of assessing the New York Heart Association (NYHA) functional classification (FC) of a patient by leveraging modern machine learning techniques. Methods: We first identified relevant quantitative data and upgraded Medly, a remote patient monitoring system (RPMS), to support data collection. We then proceeded to build six different machine learning classifiers including hidden Markov model, Generalized Linear Model (GLM), random forest and neural network based classifiers. Results: The best overall classifier was found to be a boosted GLM, which achieved a classification performance (Cohen’s Kappa statistic κ=0.73, balanced accuracy=85%) comparable to human level performance (κ=0.75). Conclusions: Although the investigated classifiers are not ready for implementation into a real RPMS, they show promise for making the evaluation of NYHA FC more universally consistent and reliable.
Heart Rate Variability Biofeedback as an Intervention Method for Reducing PTSD Symptoms in Police Officers Exposed to Trauma
Keywords: Autonomic Arousal
Biofeedback
Heart Rate Variability
Partial PTSD
Police
PTSD

PTSD has been identified as a significant occupational hazard among first responders in Canada, associated with negative health and performance ramifications. Less is known about the accumulation of PTSD symptoms among police officers (i.e., partial PTSD [P-PTSD]) and its potential impact on performance, particularly in regards to use-of-force decisions. The current project examined levels of P-PTSD symptoms among Ontarian police officers, and its relationship with occupational performance and heart rate variability (HRV). Data was extracted from an on-going study utilizing an existing HRV biofeedback intervention to reduce lethal use-of-force decision errors. Officers’ self-reported P-PTSD symptoms did not significantly predict use-of-force decision making abilities, proxies of HRV, or significantly change from pre- to 18-months post-receiving HRV biofeedback training. While significant results were not found, this pilot study provides important insight in the potential for gathering P-PTSD symptoms from front-line police officers, as well as improving health and safety in this population.
Growth and Characterization of Multicellular Spheroids in Cellulose Derived Hydrogels as an Artificial Three-Dimensional Scaffold
Keywords: Cellulose
Hydrogels
Multicellular cancer spheroids

This thesis describes the preparation and characterization of cellulose derived hydrogels. Specifically, aldehyde-modified cellulose nanocrystals (a-CNCs) and aldehyde-modified cellulose nanofibers (a-CNFs) will chemically cross-link with gelatin, forming nanofibrillar hydrogels capable of supporting the growth and differentiation of MCF 7 cells. To begin, a microextrusion-based 3D printing method was utilized to generate anisotropic hydrogel sheets. Hydrogels exhibiting both uniform and compositional gradients were extruded, resulting in gels with gradients in structure, mechanical properties and permeability. Then, MCF 7 cells were encapsulated within a-CNC/gelatin and a-CNF/gelatin hydrogels of varying concentrations in order to determine optimum cell viability. The results of these hydrogels indicate promising contributions to tissue engineering and regenerative medicine.
Adapting the Turkevich Method to Synthesize Colloidal Rhodium Nanocrystals
Keywords: nanoparticle
rhodium
transmission electron microscopy

The Turkevich method has been used widely for the synthesis of gold nanocrystals. Despite its success, it has not yet been applied to the synthesis of rhodium nanocrystals, which have great potential in myriad applications due to their special optical and chemical properties. Herein, it is shown that the Turkevich method, with the appropriate modifications, can be adapted to enable access to rhodium nanocrystals. Products are generated under a wide range of experimental conditions. In most cases, quasi-spherical aggregates of ultrasmall rhodium grains are obtained. Possible means of controlling the aggregate size are proposed. The method can also yield large, anisotropic rhodium nanocrystals, although control over the geometry of this product is not achieved. Further optimizations are suggested toward obtaining monodisperse, single-crystal rhodium nanoparticles for eventual use in applications.
A Machine Learning Approach to Distinguishing between Multiple Sclerosis and Cerebral Small Vessel Disease
Keywords: Biomedical Engineering
Biostatistics
Computer Vision
Machine Learning
Medical Imaging
Neurosciences

We sought to develop an automatic diagnostic algorithm to distinguish between relapsing-remitting multiple sclerosis (RRMS) and cerebral small vessel disease (SVD) using neuroimaging and clinical features. A mixture of t-distributions and a spatial heuristic algorithm were developed for the automatic segmentation of lesions on two MRI sequences. Combined lesion probability maps of RRMS and SVD were subsequently developed using a derivation set of patients. A novel cross entropy image distance metric was used to quantify the similarity of new cases to each disease. Bayesian learning algorithms using non-informative priors were trained using neuroimaging features and clinical features. Model hyperparameters were tuned using Monte Carlo cross validation. The model consisting of both neuroimaging and clinical features misclassified one case out of 21 on the test set when distinguishing between RRMS and SVD. As the societal and monetary cost of both diseases is high, this work has real potential for clinical impact.
Evaluation of Technology and Manufacturing Readiness Level of a Noninvasive Alcohol Biosensor Based on Wavelength-Modulated Differential Photothermal Radiometry for In-Vehicle Applications
Keywords: Biological sensing and sensors
Modulation spectroscopy
Photothermal
Photothermal effects
Spectroscopy

Drunk driving remains the most prominent cause of vehicle crashes in Canada. Among all of the countermeasures, the engineering-based control can reduce recidivism by about two-thirds. This thesis work introduces the proof-of-concept and prototype development of a wavelength modulated differential photothermal radiometry (WM-DPTR) sensor that combines the advantages of all the existing blood alcohol detection technologies. It is ultrasensitive, non-invasive, non-contact, seamless with driving task, reliable, and durable with no need for recalibration and maintenance services. This research work builds on WM-DPTR sensor’s potential for application in ignition interlock devices. The measurement results from human subjects with updated compact quantum cascade laser diode and digital signal acquisition system demonstrated the capability of WM-DPTR to detect blood alcohol concentration changes with high resolution and low detection limit. WM-DPTR limitations for applications in ignition interlock devices can be tackled by further improving instrumentation and data processing techniques.
Investigating TSPO binding in methamphetamine use disorder during early abstinence
Keywords: addiction
methamphetamine
microgliosis
neuroimaging
positron emission tomography
translocator protein

Background: It is unclear whether chronic methamphetamine (MA) use leads to brain microgliosis in living humans. We used positron emission tomography, targeting the translocator protein (TSPO) probe [18F]FEPPA, a marker suggestive of microgliosis, to explore, during early abstinence from MA, whether (1) there are changes in brain TSPO binding, suggestive of microgliosis and (2) if TSPO expression is related to “sickness” addiction-relevant symptomology. Methods: TSPO binding was measured in 10 MA users and 25 matched controls with MRI co-registration. Results: A RM-ANOVA controlling for TSPO genotype revealed no main effect of group on FEPPA VT (F(1, 32)=0.12, p=0.73). We also found no relationship between TSPO and behaviour, such as mood, craving. Conclusion: Our findings are consistent with those of post-mortem studies showing no evidence of above-normal microgliosis in chronic MA users. We also found no relationship between TSPO and addiction-relevant behavior, but replication studies are necessary to further explore this.
Effect of Alcohol Skin Cleansing on Vaccination Local Skin Reactions: A Randomized Controlled Trial
Keywords: Adverse events
Alcohol swabs
Cellulitis
Immunization
Infections
Vaccines

Objective: To assess the effectiveness of skin cleansing with alcohol in reducing the incidence of delayed pain post-vaccination, and assess the feasibility of conducting a larger trial. Methods: Participants were randomized to either be cleansed at (swab) or adjacent to (control) the injection site with 70% isopropyl alcohol then let dry before vaccine administration. Parents blinded to the treatment allocation reported local reactions for 15 days post-vaccination using paper diaries and 3 telephone surveys. Results: In 6.5 months, 170 patients were recruited and received 281 vaccine injections. Eighty-one percent of diaries were returned and 94% of parents completed all 3 phone surveys. There was no difference in the incidence of reported delayed pain or any local skin reactions between both groups. Discussion: These findings are the first evidence specifically for vaccination injections demonstrating that cleansing the skin with alcohol may not be needed.
Development of the TRAISI Web Survey Builder: Designing to Reduce Bias and Respondent Burden in Household Travel Surveys
Keywords: Household Travel Surveys
Proxy Bias
Respondent Burden
Trip Diary
Usability Testing
Web-survey

Household travel surveys (HTS) are undoubtedly the most common and amongst the largest data collection undertakings by transport agencies worldwide. Within recent years, web-based surveys have been the dominant survey mode for HTS’s. However, given the extensive detailed data collected in HTS’s, web-based HTS’s have been facing declining response rates and challenges with collecting quality data, largely due to proxy bias and poor survey designs. This study investigates methods to improve HTS data quality and reduce response burden by sharing lessons learned from the development of the TRAISI web survey builder. The study presents findings from field tests using novel features built into the platform, such as interactive maps and adaptive designs for household trip diary collection. Survey methods to reduce proxy bias, such as voluntary self and proxy reporting methods and announce-in-advance procedures, are also investigated. Overall, the study provides survey designers guidelines and recommendations for web-based HTS design.
A (M)other Talks to White Women Teachers: A Critical Autoethnography
Keywords: Anti-racist
Decolonial
Feminism
Parent engagement
White women teachers

Using critical autoethnography, I explore relationships between White women teachers and Mothers of Colour. Looking beyond a parent involvement analysis framework, I use a decolonial prism that considers colonial constructions of White Womanhood and Motherhood as critical in the mother-teacher relationship and the marginalization of Black, Indigenous, and Brown mothers in Euro-Canadian school settings. I argue that the intersecting forces of identities formulated within empire (i.e., woman, mother, teacher) multiply their oppressive potential. The antagonism that develops between the Woman-Mother-Teacher and Mothers of Colour precludes the establishment of honest, cohesive, and supportive relations, which results in harmful consequences for students of colour, their families, and their communities.
Gaussian Process Modeling and Supervised Dimensionality Reduction Algorithms via Stiefel Manifold Learning
Keywords: Active Subspaces
Dimensionality Reduction
Gaussian Process
Machine Learning
Principal Component Analysis
Random Fourier Features

Much research has gone into scaling up classical machine learning algorithms such as Gaussian Processes (GPs), but the curse of dimensionality still remains. While many supervised dimensionality reduction algorithms have been proposed in the literature, few of them can scale up to large data-sets. Furthermore, the majority of dimensionality reduction techniques are tailored for classication problems, which leaves regression tasks unexplored. The contributions of this thesis are threefold. First, we extend classical active subspace (AS) theory to a non-linear counterpart. Secondly, we introduce a scalable non linear supervised principal component analysis (SPCA) algorithm. Thirdly, we propose a novel class of supervised dimensionality reduction algorithms called smoothening analysis (SA). The SA algorithms consist of scalable linear and non-linear frequentist and Bayesian algorithms tailored (but not limited) for regression tasks that learn low dimensional Stiefel manifolds.
Rapid Coding of Scene Features via Ensemble Statistical Processing
Keywords: Ensemble
Lateral occipital cortex
parahippocampal place area
Perception
Scene
Visual neuroscience

Ensemble perception utilizes patterns in our visual field to quickly and accurately process summary statistics for multiple types of information. Typically investigated used object and face ensembles, no known experiment has addressed the statistical coding of scene ensembles, despite a neuroanatomical link between scene and ensemble perception (Cant Xu, 2012). For this study, spatially derived scene ensembles were examined, and average scene features of content (measured by levels of perceived naturalness and manufacturedness) and spatial boundary (measured by how open or closed the scene ensemble appears) were rated. It was found that: a) average ratings given for a scene ensemble will be correlated with the average of the ratings given for the individual scenes comprising the ensemble, and b) scene ensemble ratings can occur both rapidly and accurately in a fraction of a second.
A Comparison of Augmented Feedback and Didactic Approaches to Reduce Spine Motion During Box and Paramedic Lifting Tasks
Keywords: biomechanics
ergonomics
Injury prevention
low back disorder
movement (re)training
paramedic lifting

Injury prevention movement (re)training (MR) for paramedics may be improved if they were guided by biomechanical and motor learning principles. The purpose was to compare MR approaches – didactic (DID) and augmented feedback (AUG) – in reducing spine motion during lifting tasks. Untrained participants (n=26) began with a lifting test (box, medication bag, and backboard), followed by their randomly-assigned intervention involving 50 practice lifts. The DID group began with a safe lifting presentation, whereas the AUG group was coached with augmented feedback. The lifting test was performed immediately and one-week after, while spine kinematics were quantified. After one week, AUG was strictly superior to DID in reducing spine motion in the retention task but was equivalent or superior for the transfer tasks. An AUG approach to MR is supported over didactic approaches to elicit lasting changes in practiced tasks, but more training is likely required to ensure transfer to unrehearsed tasks.
Mackenzie Health: An Analysis of a “Smart” Internet of Things Approach to Healthcare
Keywords: Clustering
eHealth
Healthcare
Nursing staff
Patient call bell
Simulation

Background: Providing good quality patient care is challenging in today’s busy healthcare environment. Faster response times to patient calls have been shown to reduce the risk of falls, length of stay (LOS), and improve patient satisfaction. One hospital, Mackenzie Health has implemented a new “smart’ pilot unit with various Internet of Things (IOT) connected technologies with the goal of improving care. Methods: Data collected by the new system was statistically compared to historic data to determine the impact. A discrete simulation model was also built to explore further potential improvements in how patient calls could be routed. Results: Mean and median call response times improved by ~5% and ~31% respectively. Employing alternative call routing strategies can further improve response times and nurse travel distances. Conclusion: This study lends evidence to the argument that the adoption of ubiquitous smart technology in healthcare can improve operations and reduce inefficiencies.
A GPU-Based High Performance Particle Image Velocimetry Algorithm for Characterizing a Flow Control Actuator
Keywords: Flow Control
GPU
PIV
Turbulence

A GPU-accelerated PIV data analysis algorithm was developed. The algorithm was vigorously validated using both synthetic images and experimental data. The algorithm was run on a GPU cluster and in the best case was ∼ 10× faster than when run on a CPU. 20,000 PIV image pairs were collected and processed using the GPU-PIV algorithm to study the effectiveness of an oscillating piezoelectric jet actuator for flow control. The mean velocity and Reynolds stress data indicated two distinct regions in the actuator’s jet: one region near the nozzle exit dominated by the pulsating nature of the jet, and another downstream region which resembled a fully-developed turbulent jet. Vorticity data showed the formation of counter-rotating vortices produced by the jet near the exit. Overall, the results indicate that the actuator will be an effective flow control device.
Topology Design of Concentric Tube Manipulators Using Optimization
Keywords: concentric
optimization
robot
surgery
topology
tube

One of the major problems facing the development and road to practical usage of concentric tube continuum robots in surgical environments is that of instability. This issue, also known as the snapping problem, is caused by a tube having a high bending to torsional stiffness ratio (BTSR). Past efforts have shown that by cutting patterns on the tubes, this problem can be avoided. This thesis seeks to redesign the topology of the tubes so that BTSR is decreased and the snapping problem is resolved in a particular tube set. The generated designs were then validated through finite element analysis as well as experimental testing to demonstrate the elimination of the snapping problem. Using this novel tube design in concentric tube robotic systems can increase stable workspace because it allows the usage of greater tube curvatures and/or curve lengths. 同心管机器人的研究和应用中，操纵器的不稳定性是一个困扰研究者的严重问题，可能出现的不稳定跳动现象成为手术环境下使用同心管机器人的一大障碍。这种跳动由管子的挠度与抗扭刚度之比（BTSR, Bending to Torsional Stiffness Ratio）过高造成。过往研究表明，可以通过用机床在管子上切出方向性图案来降低BTSR值。本文旨在通过多种优化方式重新设计一套能够降低管子BTSR值的切割图案，允许操纵器在更大范围内活动而不再发生不稳定跳动。管子的模型通过拓扑优化生成，且每根管子的性质都由有限元分析得来。如此，我们能在生产样本之前有大量不同尺寸管子的设计，从而对其刚性和受力效果作出判断。我们对切割完的样本测验得出其真实BTSR值。结果显示，设计出的管子的BTSR值被有效降低，在同心管系统中使用时，被切割过的同心管操纵器在运动中没有出现不稳定的跳动现象，这样设计出来的同心管操纵器可以直接扩大操作空间，并增加可到达的坐标。本文的结论有助于同心管机器人早日在手术中得到应用。