VictorJuiz/thesis huggingface dataset:
Understanding the Behaviour of GFRP Reinforced Concrete Members under Changing Climate Trends
Keywords: climate change
durability
fiber reinforced polymers
GFRP
reinforced concrete
shear

While fibre-reinforced polymers (FRP) bars have significant advantages over steel with respect to resistance to corrosion, high strength-to-weight ratio, and magnetic neutrality, FRP bars can still deteriorate when exposed to extreme weather events. The current research investigated the effects of increased temperatures, resulting from recent climate changes, on the behaviour of GFRP bars by testing several specimens: 46 coupons, 37 bond specimens, and 12 large beams. The experimental investigation—divided into three phases—was later followed by the analytical study. In the first phase, the tensile behaviour of GFRP bars for elevated temperatures up to about 300oC was studied. Results showed that GFRP bars experienced about a 60% reduction in strength at a steady-state temperature of 250oC. The bars subjected to 40% of the room temperature strength and exposed to high temperatures resulting from situations such as sudden fire sustained the load for about 50 minutes. In the second phase, bond behaviour was studied with pullout as well as beam bond specimens which were conditioned at 50oC and 80oC for four months under a relative humidity of 60%. It was found that the studied thermal conditioning induced up to 26% reductions in the bond strength of GFRP bars. Moreover, beam specimens yielded lower bond stresses at room temperature and experienced higher thermal degradation than their counterpart pull-out specimens. The long-term thermal performance of flexural and shear critical beams was studied in the third phase. Beams were conditioned at 50oC for four months under 60% relative humidity. Under-reinforced flexural critical beams showed about a 22% reduction in the ultimate failure load, but over-reinforced beams did not observe substantial reductions in the ultimate capacity. Likewise, the shear critical beam did not observe a significant reduction in the ultimate shear capacity. Finally, a database of more than 500 coupon specimens tested under elevated temperatures was developed based on which statistical analysis was carried out, and a model is proposed to evaluate the reduction in the tensile strength of GFRP bars with increasing temperatures. Moreover, an analytical model is developed to predict the shear capacity of GFRP-RC beams.
Hierarchical Manufacturing of Hybrid Multi-Functional Soft Actuator
Keywords: hybrid nanocomposite
multi-functional material
multi-stimuli-responsive material
self-sensing actuator
soft actuator

As the use of mechanical actuator becomes more unfeasible in this world that require flexibility and light-weight products, an alternative solution is needed that is beyond the capabilities of current single stimuli-responsive and single functioning soft actuators. The limitations of a single function (actuation) powered by a single external stimulus hinders its practicality for real-world applications that is comprised of integrated systems. This thesis presents a series of studies in the development of multi-stimuli-responsive and multifunctional soft actuators, with unlimited potential in function and power source, and ultimately better suited for the application at hand. Single stimuli-responsive soft actuation systems were carefully studied for successful integration into multi-functioning hybrid composites, starting with piezoelectric polymer actuator where nanofillers were embedded to increase its actuation magnitude. As a gripper system, hybrid pneumatic-magnetic soft actuator was able to increase its degree of freedom in actuation and demonstrate multi-plane actuation with increased blocking force. With robust actuation, its application went beyond traditional grippers and was able to move itself to complete an LED circuit and demonstrate its actuation in air and water environments. For smaller actuation, such as vibration dampers, a hybrid piezoelectric-magnetic self-sensing actuator (HPMSA) in a thin film device was utilized highlighting simultaneous alignment of multiple nanofillers and crystals for enhanced sensing and actuation properties. By applying 3D printing, the same HPMSA could be fabricated in greater size to sense and dampen excessive vibrations that are harmful to vehicle passengers. This fast and scalable fabrication method allows the possibility of mass production and commercial use, easily producing thin films of same properties. The results of this research can be used to further the development of multi-stimuli / -functional soft actuators to enhance actuation performance and take a step closer to replacing mechanical actuators and actuator systems in its entirety.
Development of an Ultrasonic Bone Cutting Instrument for Robotic-assisted Surgery
Keywords: bone cutting
craniofacial
robotic
surgery
teleoperated
ultrasonic

The use of robotic assistance in abdominal surgeries has increased rapidly in the last two decades and da Vinci Surgical System (dVSS) variants by Intuitive Surgical are now used in over one million procedures annually. With the widespread availability of the dVSS and the release of competing teleoperated systems anticipated in the near future, there is motivation to investigate whether non-abdominal operations may also benefit from the advantages provided by these robotics systems. Several research groups, in early feasibility studies, have found benefits of using the dVSS for operations in which hard tissue removal is required, including transoral, orthopaedics, spinal, and neurosurgery. However, the application of the robot in craniofacial procedures remains unexplored. It is hypothesized that the robotic-assisted system, with its improved precision, motion scaling, and advanced visualization, may similarly provide benefits in both minimally invasive and open cases of craniofacial surgery. However, the lack of robotic instruments for hard tissue precludes exploration in craniofacial procedures and remains a blocker for evaluating a fully robotic approach in operations where any hard tissue removal is required. The research presented here intends to address this limitation by developing a ultrasonic bone cutting instrument for the dVSS, and then evaluating the initial feasibility of using the system for craniofacial operations by performing a simulated procedure. To develop the prototype, performance and clinical requirements were first established and the instrument was designed and optimized using finite element analysis and a commercially available multi-objective genetic algorithm. The prototype was then verified using a combination of amplitude characterization, fatigue testing, and experimental modal analysis. Benchtop testing indicated the optimal cutting approach based on cutting depth, speed, and approach angle, and teleoperated cutting tests were performed on representative craniofacial models using an open approach. Initial experiments show that teleoperated bone cutting using an ultrasonic tool is feasible despite the lack of force feedback provided by the robot, and results indicate that there may be improvements to accuracy over manual tools. Further testing in a minimally invasive model with additional participants is required to evaluate robot setup, reach and range of motion of the prototype instrument, operating time, and safety
Towards Trustworthy Machine Learning in High-Stakes Decision-Making Systems
Keywords: decision-making systems
fairness
machine learning
neural networks
robustness
trustworthy machine learning

Machine learning systems are increasingly applied to tasks of high-stakes decision-making, in areas like healthcare, personal finance, and criminal justice. In these areas, the trustworthiness of the system is essential; beyond just having a high-accuracy tool, a number of other desiderata are required. Stressing that creating trustworthy machine learning is a problem without a well-defined solution, we focus in particular on two of these desiderata: fairness and robustness. To these ends, we discuss three potential approaches to improving the trustworthiness of machine learning systems. In the first, we consider the task of learning representations which guarantee that downstream classifiers yield predictions that align with fairness metrics when trained on transfer tasks, demonstrating how designing an adversarial loss function can correspond to various commonly-used fairness metrics. In the second, we provide an intuitive heuristic for detecting underspecification, show how it can be computed in a post-hoc fashion using only second-order statistics of the trained model, and discuss how we navigate computational hurdles for calculating this score in deep neural networks using techniques for eigenspectrum estimation. In the third, we reframe rejection learning as a task which should be inherently adaptive, depending on the properties of external decision-makers, and show how to formulate this as a mixture-of-experts-type learning objective, studying its impact on both fairness and accuracy. Through theoretical analysis and empirical evidence, we examine the strengths and weaknesses of each approach, and critically discuss how each fits into the larger project of building trustworthy machine learning systems.
Evolutionary Consequences of Plant Genome Structure
Keywords: Genome structure
Introgression
Plant evolution
Polyploidy
Recombination
Transposable elements

The outcome of evolutionary forces in natural populations is contingent on an organism’s genome structure, which itself varies and evolves. My thesis uses population genomics to investigate a range of evolutionary questions and processes broadly related to plant genome structure. In chapter 2, I review literature of the genomic landscape of transposable elements, recombination rate, and their interactions, and discuss the implications for their coevolution. In chapter 3, I show that how recombination and selection interact to determine the landscape of introgression from Capsella rubella into Capsella grandiflora varies by scale and is dependent in the largest scale on the length of chromosome arms. I find no evidence that selection against introgression is due to deleterious load or loci associated with floral evolution, but I show a strong reduction in introgression at the locus causing the breakdown of self-incompatibility. In chapter 4, I use genome assemblies of 32 species in the Brassicales to investigate the role of polyploidization in shaping the variation of genome size and transposable elements, as well as convergent and lineage-specific selective responses in evolutionarily conserved sequences. In chapter 5, I show that Rumex hastatulus, a species with large low-recombination regions across the genome, has a low efficacy of selection and unexpected patterns of chromosome-wide genetic diversity. I show that models of linked selection do not predict the genomic landscape of diversity, suggesting that an ongoing history of genomic rearrangements may be obscuring patterns of both recombination and diversity in the species. Overall, my thesis highlights the importance of considering genome structure as both shaping the evolution of plants and as a complex set of phenotypes evolving in concert and in conflict with the organism.
Once Upon a Time in the Oeste: Epic, History and Narrative in Iberia
Keywords: Camões
Epic
Historiography
Iberia
Narrative
Philosophy of History

This dissertation explores the boom of epic poetry from 1569 to 1600 in Iberia and the Iberian epic genre’s engagement with history. It contends that the engagement of sixteenth-century Iberian epic with recent history, with contemporary philosophy of history, and historiography, makes Iberian epic distinct from other epic poetry. Every epic of this period is about a recent colonial event, drawing ideas from contemporary historical writing, and explicitly and implicitly thinking about the nature of history and time. As a distinctly historical genre, Iberian epic forms a body of texts about early imperial and colonial history from which historians can gain important historical perspective, as well as containing its own philosophy of history.The first chapter of this dissertation defines the genre of Iberian epic, detailing its influences from classical and Italian epic, exploring how it engages with history in ways other epics do not. In particular, the critic Miguel de Faria e Sousa’s extensive analysis of Luís de Camões’ Os Lusíadas is explored as a framework for understanding the contemporary conception of Iberian epic. The second chapter explores historical writing in sixteenth-century Iberia, focusing on the important and expansive Portuguese historiographies about India by João de Barros, Fernão Lopes de Castanheda, and Gaspar Correia, detailing how these texts define history, the sources they use, and their rhetorical norms. The chapter then compares how these historiographies describe key historical moments (Vasco da Gama’s first journey, contact with Africa, or military and diplomatic clashes with Muslims) with the description of the same or similar events in Iberian epics, such as Jerónimo Corte-Real’s Cerco de Diu, Juan Rufo’s Austriada, Juan Latino’s Austrias Carmen, and Alonso de Ercilla y Zuniga’s La Araucana, among others. The final chapter conducts a close analysis of Os Lusíadas, the most famous epic from this period. My analysis of Camões’ epic details how the poem’s plot and many narrators, structure history in a way that both celebrates Portuguese empire and subversively critiques it, arguing for the importance of poetry and narrative in preserving history.
Cognitive Decline in Parkinson's Disease: Understanding the Pathophysiological Differences
Keywords: beta-amyloid
Cognitive decline
dopamine
MRI
Parkinson's disease
PET imaging

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, and the accompanying cognitive decline sequelae are one of its most pressing and least understood non-motor symptoms. It is estimated that between 20 to 40% of PD patients have some form of cognitive decline at the time of diagnosis, and over 80% of PD patients eventually convert to dementia within 20 years of diagnosis. PD patients can experience deficits in executive function, memory, attention, language and visuospatial function. PD has been linked to many different forms of pathology, ranging from brain atrophy and functional dysregulation, toxic protein deposition, and neurotransmitter system dysfunction. However, it is still not well understood why some PD patients experience rapid cognitive decline while others remain cognitively stable for years. Brain imaging techniques can be used to help elucidate the pathophysiological changes that occur which separate cognitive decline from cognitive sparing, providing insight into the compensatory changes the brain undergoes to maintain healthy cognition. The general aim of this thesis was to uncover the brain differences between PD patients with and without cognitive decline using multimodal imaging techniques and machine learning assisted modelling. First, using a coordinate-based meta-analysis, we found that key hub regions in three different important brain networks were affected by structural atrophy and functional hypometabolism in PD patients with cognitive decline: the bilateral insula, the bilateral dorsolateral prefrontal cortex, and left angular gyrus. Second, we used graph theory analysis to uncover that cognitively spared PD patients had more efficient brain networks than PD patients with mild cognitive impairment, suggesting compensatory network reorganization was occurring to maintain healthy cognition in the face of increasing disease burden. Finally, we found evidence that region beta-amyloid deposition affects cognitive decline in PD, with some brain regions being more vulnerable to the burden than others. Taken together, this thesis posits various ways the brain experiences both compensatory help and pathological harm due to PD cognitive decline pathology, providing a better understanding of this complex symptom umbrella.
Sim-Cyberpunk: Serious Play, Hackers and Capture the Flag Competitions
Keywords: Capture the Flag
Cybersecurity
Game Studies
Hacker Culture
Hacker Studies
Information Security

Capture the flag (CTF) is a style of game developed within the hacker community to simulate/emulate the practice of vulnerability research. In a CTF players identify security vulnerabilities in information systems and exploit these flaws to undermine their operations, which gives them access to a “flag” which they score for points used to win a competition. An exploratory study of this game, this dissertation uses ethnographic methods including observation of three CTF competitions and semi-structured interviews with 47 CTF players and designers. Analysis of this data considers the co-constitution of the game through the practices of its designers and players, concerning the values of the hacker community and its linkages to the information security industry whose membership constitutes the preponderance of CTF participants. Utilizing Sara Grimes and Andrew Feenberg’s (2009) theory of “games as sites of social rationalization” this paper argues that CTF has been instrumentalized as a tool of cultural reproduction. This function of CTF is used to discursively shape and sustain knowledge acquisition, identity formation and work in the cybersecurity industry through the affordances of play in alignment with hacker values, translating intellectual capital into social capital through playful game systems.
Theory of Mind Reasoning in Explanation, Plan Recognition, and Assistance: Theory and Practice
Keywords: Epistemic Planning
Plan Recognition
Theory of Mind

With the rapid advancements in the field of artificial intelligence (AI) in recent years, one of the longstanding goals of the field – building AI systems that are able to interact with other agents in social settings – may appear within reach. However, present-day AI systems do not yet demonstrate the social cognitive skills needed to robustly operate in the real world, and in particular in complex social settings involving humans. Research on humans has identified that Theory of Mind – the ability to attribute mental states (e.g., beliefs, desires, and intentions) to oneself and to others – is a precursor to the development of social cognitive abilities that enable most humans to successfully navigate complex social settings. It follows, then, that augmenting AI systems with Theory of Mind capabilities could improve upon their existing social cognitive abilities and get us closer to achieving AI’s aforementioned longstanding goal. In this dissertation, we present a body of work that investigates the role of Theory of Mind in explanation, plan recognition, and assistance and takes steps towards the betterment of social cognitive abilities held by present and future AI systems. Moreover, in much of this dissertation we appeal to the computational paradigm of epistemic planning, which allows us to address or circumvent some of the challenges involved with augmenting AI systems with Theory of Mind. Appealing to epistemic planning allows us to develop computational solutions and demonstrate the feasibility and usefulness of Theory of Mind in explanation, plan recognition, and assistance. Finally, this dissertation employs these computational solutions and integrates them within a robotic system that demonstrates social cognitive abilities in complex real-world settings, as well as a potential to benefit humans with whom it interacts.
Recycling of LiNixMnyCo1−x−yO2 (NMC) Cathodes from End-of-Life Lithium-Ion Batteries Using Hydrometallurgical and Direct Recycling Processes
Keywords: Direct recycling
Electric vehicles
Hydrometallurgy
Lithium-ion batteries
NMC cathodes

Lithium-ion batteries (LIBs) have become a mainstream power source for portable electronic devices and electric transportation due to their several prominent advantages, including high energy density, long storage life, small volume, lightweight, and low self-discharge. With the increasing demand for LIBs, the serious shortage of raw materials for LIB production, and the growing global awareness to protect the urban environment, recycling of postconsumer LIBs has become imperative. In recent years, LiNixMnyCo1−x−yO2 (NMC) cathode material has become the most promising cathode material for LIBs because of its low cost, high discharge capacity, good cyclic performance, and stable structure; thus, its application in electric vehicles (EVs) has been promoted. Since this cathode material will soon enter the recycling stream, it is critical to have an effective recycling process for its handling. The overall objective of this dissertation is to develop novel, efficient, and sustainable hydrometallurgical and direct recycling processes for NMC cathode materials from spent LIBs. This dissertation is focused on 1) recovering lithium, nickel, manganese, and cobalt from NMC cathode material of spent LIBs of an EV via acid leaching; 2) separating all four metals from the leachate after acid leaching using electrodialysis; 3) synthesizing nickel-rich NMC cathode material for LIBs utilizing supercritical CO2; and 4) directly recycling degraded NMC cathode material of spent LIBs from an EV using hydrothermal relithiation combined with sintering. The milestones in this dissertation involve 1) developing, advancing, implementing, and optimizing the leaching, metal separation, coprecipitation, and relithiation steps to improve the hydrometallurgical and direct recycling routes by reducing the environmental impact and enhancing the sustainable development; and 2) elucidating the leaching, electrodialysis, coprecipitation, and relithiation mechanisms using fundamental investigations and kinetic modeling. The potential for social, environmental, and economic impacts through innovations and scientific excellence of this dissertation is immense. The advantages of successful implementation of this research project are twofold: 1) it provides a secure secondary supply for strategic materials that face steep demand growth and potential supply shortfall; and 2) it provides an environmentally sustainable and economic route for waste valorization and resource recovery, which in turn will enable the circular economy.