VictorJuiz/thesis huggingface dataset:
Design, Characterization, and Performance of Adsorptive Membranes for Nutrient Recovery from Water

The discharge of excess nutrients, such as phosphorous (P) and nitrogen (N), from wastewater treatment plants (WWTPs) can lead to water eutrophication, which can harm aquatic ecosystems. Traditionally, nutrient removal is achieved through chemical and biological processes. However, with more stringent regulations on discharge, these traditional methods may not be able to meet the desired levels of removal. Moreover, these methods do not offer the possibility of recovery and produce waste for subsequent handling. Adsorptive nanoparticles are a promising option for removing nutrients from wastewater as it offers a chance for recovery, high selectivity, and efficient removal even at low initial concentrations. However, the widespread application of this technology is hindered by challenges associated with the effective removal of adsorption media from water, particle agglomeration in solutions, and fear of leaking. This issue may be addressed by immobilizing adsorbing nanoparticles in/on highly porous polymeric matrices, such as phase-inversion membranes (PIM) and electrospun nanofiber membranes (ENMs). This study focused on the fabrication of adsorptive membranes containing akageneite for the recovery of P from water. Three types of membranes were produced, each with different fabrication processes. The first membrane was an ENM modified with a cationic surfactant called benzyldimethyldodecylammonium chloride (BDDA). Results showed that the addition of BDDA improved the capacity for P adsorption due to increased hydrophilicity and the Donnan membrane effect. The second membrane was a polydopamine-coated PIM, which was created using a novel two-step in-situ mineralization process with NaOH. The third membrane was a PIM fabricated through the simple process of particle blending in polymer solution. All three membranes demonstrated high affinity for P and excellent reusability. Akageneite particles were also stable in all membranes owing to the chemical compatibility (i.e., the presence of polar functional groups) between polymer and inorganic filler. However, the third membrane achieved higher uptake per unit area of the membrane, owing to the higher particle loading which was only possible through this technique. The phase-inversion process was also used to fabricate highly permeable adsorptive polyacrylonitrile membranes embedded with zeolite 13X for N recovery from aqueous solutions. These membranes proved effective in batch and dead-end filtration studies using single-solute, binary, and synthetic wastewater solutions. They were also able to maintain their uptake abilities of target ions even after 5 regeneration cycles. Adsorptive membranes offer an innovative solution to water purification challenges by combining the high permeability of low-pressure membranes with the high selectivity of inorganic adsorbent particles.

Keywords: Adsorption
Ammonium
Membrane fabrication
Nutrient recovery
Phosphorus
Wastewater treatment
Advisor: Farnood, Ramin
Tabe, Shahram
High Through-put Screening Studies of Intercellular Cell Interactions for Small Cell Clusters using a Microfluidic Device

Two primary projects were completed in this work in biochemistry and physical chemistry, where cell-cell interactions and liposome-encapsulated metal nanoparticles were investigated, respectively. The aim of the biochemistry project is to understand cell-cell interactions between immune cells and acute myeloid leukemia (AML) cancer cells in cell pairs or small cell clusters in alginate microgels in 3D rather than the conventional 2D. First, a microfluidic device was employed and optimized to produce microgels containing both cell types in a high throughput manner. These inert and bio-active hydrogel biomaterials were employed to mimic extracellular matrix (ECM). Hydrogels traditionally used for bulk cell encapsulation were used to produce micrometer-sized hydrogel beads, known as microgels, which provide confined microenvironments for the cells. These microgels had a diameter of around 50μm and can be utilized as individual cell culturing units. Specifically, inert alginate hydrogels were used to study the cell-cell interactions under environments without additional stimulation. The hydrogel parameters were optimized for both THP1 macrophage and HL60 cancer cell encapsulations including flow rates and inlet cell concentrations. The chemical and mechanical properties of the resulting microgels were investigated by obtaining Young’s modulus of the microgels with different alginate and Ca2+ concentrations. The interactions between the cells were measured in terms of changes in surface marker levels and phagocytosis after treatments. To further promote the migration of macrophages thus phagocytosis in different compartments of each microgel, modifications were made to the alginate scaffold by introducing gelatin-methacryloyl (GelMa), a semi-synthetic hydrogel which consists of gelatin derivatized with methacrylamide and methacrylate groups.This cell-in gel system offers a detection model for various cell types to develop cancertherapies. The second project focused on developing a system of liposome-encapsulated Rhodium nanoparticles (RhNPs) for Raman enhancement of phenylalanine (Phe). The RhNPs were synthesized and characterized while the liposomes were produced, followed by sonication to encapsulate the RhNPs in liposomes. The Phe was then introduced to the system and examined by Raman spectroscopy after incubation for 6 hours. Two distinct peaks and an overtone were observed and analyzed. This result suggests the strong light scattering is due to surface-enhanced resonant Raman scattering.

Keywords: Cell culsters
Cell interactions
Hydrogels
Microfluidics
Raman scattering
Advisor: Walker, Gilbert
Analysis and Design of Distributed MIMO Wireless Networks

In the realm of wireless communications, geographically distributing the serving antennas is pivotal to harness the full potential of multiple-input multiple-output (MIMO) technology. By strategically positioning the network's transmitters, herein called access points (APs), in close proximity to users, we strengthen the desired signal while capitalizing on macro diversity and cooperation. Numerous architectures have been proposed for distributing the antennas and setting cooperation. Herein, we focus on the emerging network scheme called the user-centric cell-free massive MIMO (UC-mMIMO) network. In the first part of this thesis, we consider the problem of placing the APs through a wireless fronthaul. We analyze two possible MIMO fronthaul solutions: multicast and zero-forcing beamforming. Using these solutions, we develop a statistical model that maximizes the achievable rate on the access channel while respecting a fronthaul outage constraint. In this part, we focus on a cell-centric clustering scheme. In the second part, we handle the problem of user-scheduling and beamforming in the UC-mMIMO scheme. We propose two different paradigms for resource allocation. The first is centralized resource allocation scheme where user-scheduling and beamforming are performed at a central unit (CU) located at the network core. The second is distributed or decentralized resource allocation with two variants of decentralization; which we denote as the AP-distributed system and the CU-distributed system. In the third part, we study the management of handoffs (HOs) within the UC-mMIMO network scheme. Due to the user-centric clustering and the dense deployment of the APs, a moving user may frequently encounter HOs, where HOs entail the addition/removal of APs to/from the serving set of the user. This potentially could affect the system performance. We propose two distinct methodologies for the management of HOs within the UC-mMIMO context. The first approach involves modeling HOs as a partially observable Markov decision process (POMDP), where we adopt a divide-and-conquer approach to obtain a HO policy using the value iteration algorithm. While the second approach harnesses the power of reinforcement learning, where we use deep reinforcement learning (DRL) to construct a deep neural network (DNN)-based HO policy that exhibits real-time control and low computational complexity.

Keywords: Deep Reinforcement Learning
Distributed Antenna System
Machine Learning for Wireless Communications
Telecommunications
User-Centric Cell-Free Massive MIMO
Wireless Networks
Advisor: Adve, Raviraj
Shahbazpanahi, Shahram
On Meeting a Maximum Delay Constraint Using Reinforcement Learning in Wireless Networks

Latency plays a key role in a wide range of applications. Ultra-reliable low-latency communications is often a crucial requirement for many applications such as autonomous driving, financial trading, remote healthcare, public safety, wireless sensor networks, etc. Such applications have in common strict requirements in terms of capacity, hard end-to-end latency constraints and high reliabilities. Considering the requirements of such applications, average delays are not of interest given that an instantaneous disruption in the transmitted data will lead to a poor performance of the overall system. Furthermore, in applications such as public transportations, for instance, different objects face different priority levels as well as tolerable deadlines to be served. In this work, our main goal is to consider scheduling a given number of flows with random packet arrivals, with/without prior knowledge about the packet statistics, and a hard latency constraint (maximum tolerable delay) in the downlink of a wireless communication network. We wish to minimize the dropping of packets that comprise these flows; however, finding the optimal schedule for a set of flows is NP-hard. This is the motivation for our work: we wish to find an efficient approach to tackle the scheduling problem in a realistic large-scale scenario. To the best of our knowledge, in considering the issue of latency, most state-of-the-art technologies focus on the average delay (which can, often, be translated into a throughput constraint). Those addressing the hard delay constraint suffer from several limitations in large-scale probabilistic environments. We consider the scheduling problem for both cases of having or not having prior knowledge of the statistics (e.g., flow arrival rates). First, we address the scheduling problem with the full knowledge of the statistics and in this regard, we benefit from reinforcement learning (RL). Second, as the first work in this area, we use inverse RL (IRL) in case no prior knowledge of flow arrival rates is available. Our proposed techniques can be applied to not only our problem of interest discussed in this work, but also can be used for any large-scale probabilistic sequential decision making problem with delay-sensitive packets. If the problem parameters change over the time horizon, online learning is essential; this is what the proposed approaches can provide.

Keywords: Max-delay Constraint
Monte Carlo Tree Search
Reinforcement Learning
Scheduling
Traffic Prediction
Advisor: Adve, Raviraj S.
The Effects of Automation Transparency on Human Performance

Creators of automated systems are increasingly called upon to make their systems transparent. However, contrasting interpretations of the connotation of transparency complicate the systems engineering process. We conducted a scoping review that maps out differences in the automation transparency notion based on origin, historical trends, and operationalization consistency. We discovered that transparency had been used with two opposite meanings in the human-automation interaction literature: seeing-into versus seeing-through, the internal process of automation. The seeing-through connotation embrace consistent objectives and approaches, whereas seeing-into connotation reflect significant divergence in the same dimensions. We demonstrated a variety of transparency design objectives, which regulators can leverage to determine the effectiveness of transparent systems reliably. In addition, we conducted a review of four seeing-into transparency models. This review assists researchers in assessing the suitability of the models for designing transparent systems.Prior studies have shown conflicting results about the impact of seeing-into automation transparency (i.e., information disclosure about automation) on human performance. We conducted an experiment with 24 participants to investigate the impact of transparency in a decision aid guided by a Machine Learning model on human performance measures. The results on state estimation, automation reliance, trust, workload, and self-confidence were not statistically significant. This study showed that disclosing information about a decision aid’s rationale does not necessarily impact operator performance. Given the results of our experiment, we were interested in exploring the effects of seeing-into transparency on task performance with greater statistical power than afforded by any one study through a meta-analysis. However, the lack of a systematic and operational definition of seeing-into transparency intervention complicated the meta-analysis. Therefore, we assessed the complexity of automation transparency intervention and created a logic model that characterized its mechanisms. Finally, we conducted a meta-analysis, a statistical assessment of the magnitude and consistency of the observed effects of automation transparency interventions on task performance. Contrary to the common narrative claims, this meta-analysis demonstrated little evidence that automation transparency is a generalizable principle with regard to its impact on task performance. The effects of automation transparency on trust, situation awareness, and workload remain to be investigated.

Keywords: automationtransparency
meta-analysis
transparency
Advisor: Jamieson, Greg GR
Enhancing Parental Role in Managing Pain in Neonates

Infants are exposed to a variety of painful procedures in the first year of life. Infants admitted to NICUs are exposed to repeated painful procedures. Repeated and prolonged exposure to pain is known to have detrimental neurodevelopmental side effects. Therefore, reducing pain in these infants is of key importance. Evidence supports a variety of non-pharmacological pain reducing strategies that are still not consistently used. Parents are a potential untapped resource for helping to improve infant pain management. This program of research was designed to investigate the facilitators and barriers to parental participation in infant pain management, determine the impact of parental education on utilization of pain management strategies, explore parents’¬ experience with pain care, and describe perceptions of an educational bundle to increase parental involvement. The Parental Involvement in Neonatal Pain Management conceptual model guided this research and additional, the COM-B model was utilized in the third study. The first study, a metasynthesis of qualitative literature, demonstrated parents have the desire to learn and participate in their infant’s pain management but their lack of knowledge, the NICU environment and health care providers’ behaviours impact their ability to participate. The second study, a systematic review and meta-analysis, demonstrated parental education provided improved utilization of pain management strategies for the infants but it was unclear how to best educate parents. The third study, an exploratory descriptive qualitative study, supported parental beliefs, information/support, and parent-infant proximity as important factors in parents’ participation in their infant’s pain management. Parents desire to be involved; however, they require knowledge and support from health care providers (HCPs) to attain this involvement. HCPs were both facilitators and barriers to parent participation. The educational bundle developed for the study, including a book, videos, and posters, was well received by parents. Parents reported learning new knowledge and self-efficacy regarding future participation. Educating and supporting parents to provide pain management strategies for their infants has the potential to improve pain management in their infants and potentially improve their long-term outcomes.

Keywords: infant pain
infant pain management strategies
parental education
Advisor: Taddio, Anna
Absorption-Dominant Electromagnetic Interference Shielding Polymer Composites and Foams

The development of conductive polymer composites (CPCs) and foams offers a promising solution for achieving absorption-dominant electromagnetic interference (EMI) shielding while mitigating secondary electromagnetic pollution. Despite the significance of structural and geometrical factors in creating high-performance absorption-dominant EMI shielding materials, systematic structure-property (i.e., EM wave reflection efficiency) relationships have rarely been reported for these materials. Therefore, this dissertation aims to demonstrate how theoretical computation and experimental design can be integrated to overcome the challenges of structural design and optimization of absorption-dominant EMI shielding CPCs for cutting-edge applications.The first part of the thesis includes an in-depth understanding of the effects of cellular structure and geometry on the EMI shielding properties of single-layer EMI shielding CPCs and foams. An input impedance model was applied to explore the thickness dependency of reflectivity (R) in microcellular CPC foams and then decouple the effect of thickness on the R-value from other structural variables, such as the void fraction and cellular morphology. In particular, the presence of microcellular structure can effectively tune the input impedance matching while maintaining a satisfactory EMI shielding effectiveness, resulting in a reduced R and enhanced absorption-to-reflection ratio at optimal thickness. The second part of this thesis demonstrates a theoretically guided approach to designing and fabricating bilayer gradient CPC systems that offer advanced absorption characteristics for EMI shielding. These systems comprise an absorption layer that dissipates the EMI energy and a shielding layer that reflects and shields the remaining energy. Heterostructured SiC nanowire/MXene (Ti3C2Tx) nanosheet hybrids were developed in the absorption layer via interface engineering, which revealed an improved EM energy dissipation capability and satisfactory impedance matching in theoretical results. Moreover, the input impedance of the bilayer CPC systems can be effectively tuned by optimizing the microstructure and geometry of both absorption and shielding layers via theoretical computations, achieving absorption-dominant EMI shielding performance with broadband ultralow reflectivity and a controlled sample thickness. This dissertation developed a fundamental understanding of structure-property relationships and proposed new methods to develop and fabricate CPCs and foams for achieving high-performance absorption-dominant EMI shielding.

Keywords: Advanced Manufacturing
Conductive Polymer Composite
EMI Shielding
MXene
Polymer Foam
Advisor: Park, Chul B.
Emerton-Gee Stacks, Serre Weights, and Breuil-Mézard Conjectures for GSp_4

We construct a moduli stack of rank 4 symplectic projective étale (phi,Gamma)-modules and prove its geometric properties for any prime p>2 and finite extension K/Q_p. When K/Q_p is unramified, we adapt the theory of local models recently developed by Le-Le Hung-Levin-Morra to study the geometry of potentially crystalline substacks in this stack. In particular, we prove the unibranch property at torus fixed points of local models and deduce that tamely potentially crystalline deformation rings are domain under genericity conditions. As applications, we prove, under appropriate genericity conditions, an GSp_4-analogue of the Breuil-Mézard conjecture for tamely potentially crystalline deformation rings, the weight part of Serre's conjecture formulated by Gee-Herzig-Savitt for global Galois representations valued in GSp_4 satisfying Taylor--Wiles conditions, and a modularity lifting result for tamely potentially crystalline representations.

Keywords: automorphic representation
Galois representation
Generalized Serre weight conjectures
Langlands Program
Advisor: Herzig, Florian
CyberBullying and Schools' Organizational Capacity

Despite the implementation of numerous policies to combat cyberbullying, its prevalence remains a significant concern. This qualitative study examines the organizational capacity of schools in dealing with cyberbullying. Interviews were conducted with various stakeholders in 22 public and Catholic schools across Ontario, Canada, including principals, vice-principals, social workers, police officers, parents, and students. The study aimed to assess the efficacy of school initiatives and policy tools and determine the extent to which schools possess the capacity to address cyberbullying effectively.Findings revealed that among the 22 schools studied, seven were deemed to have unhealthy climates and lacked the necessary capacity to tackle cyberbullying. All schools were reactive, responding only after incidents were reported, and held the misconception that an absence of reporting indicated the absence of bullying. Moreover, all schools demonstrated some degree of organizational capacity deficit. In the weakest schools, staff exhibited indifference towards cyberbullying, allowing it to persist. Most schools engaged in symbolic actions, such as organizing Pink Shirt Days and Anti-Bullying weeks, without implementing standardized, evidence-based approaches to prevention and intervention. Although schools demonstrated organizational capacity in raising awareness and addressing reported cyberbullying cases, their ability to detect and prevent underreported instances was limited. Staff’s sense-making efforts regarding cyberbullying were influenced by administrators, yet none of the participants reported strong leadership from principals in implementing provincial and board policies. Consequently, teachers and other staff faced challenges in defining cyberbullying and accessing quality models for addressing this social issue. This study highlights the urgent need for schools to enhance their organizational capacity to effectively address cyberbullying. It emphasizes the importance of proactive measures, standardized approaches, and leadership at the administrative level to foster a culture of prevention and intervention. By gaining a deeper understanding of the limitations in organizational capacity, schools can develop comprehensive strategies to combat cyberbullying and ensure the well-being of students in the digital age.

Advisor: Zuker, Marvin
Ryan, Sherida