VictorJuiz/thesis huggingface dataset:
The Effects of Chemotherapy Treatment for Hodgkin Lymphoma Cancer on the Singing Voice
Keywords: chemotherapy
Hodgkin Lymphoma
music
pedagogy
singing
voice

Hodgkin Lymphoma is a cancer of the lymphatic system in which the disease spreads from one lymph node group to another. A combination chemotherapy treatment known as ABVD (Adriamycin, Bleomycin, Vinblastine, Dacarbazine) is commonly used to treat Hodgkin Lymphoma. Chemotherapy can have strong negative impacts on the body and specifically, the singing voice. Although there are multiple sources related to treatment protocols for laryngeal, thyroid, breast and other cancers, there are few studies associated with Hodgkin Lymphoma or how ABVD chemotherapy treatment might affect the singing voice. To date, there are limited resources that inform singers and voice teachers on coping strategies for maintaining vocal health during chemotherapy treatment. Further, there is limited information on how chemotherapy treatment and cancer-related medications might affect general health, breath management, vocal stamina, range, or ensuing repertoire choices. This study aims to investigate the effects of standard chemotherapy treatment for Hodgkin Lymphoma cancer on the singing voice. The study addresses two research questions: 1) What are the effects of ABVD chemotherapy for Hodgkin Lymphoma cancer on the singing voice? and 2) Are the effects of chemotherapy on the singing voice heard by Expert Listeners in the vocal field? To answer the first research question, a Singer Questionnaire is used to interview cancer patients on the perceived effects of chemotherapy on their voices. I also reflect on my experience of chemotherapy on my singing voice. To answer the second research question, voice professors, pedagogues, and speech-language pathologists (Expert Listeners) listened to recordings that I made of my voice pre-chemotherapy, during, and post-chemotherapy, and they rated specific vocal characteristics using devised rating scales. I describe how ABVD chemotherapy and antiemetic medications affect the following parameters of the voice: range, resonance through vowels with dynamic contrasts, and staccato to legato articulation through vocal exercises and one song. With the data, written feedback, and my personal experience, this study will provide information to singers and singing teachers on the possible anticipated effects of ABVD chemotherapy on the singing voice and give insight into what vocal changes may occur during chemotherapy treatment and while taking antiemetic medication.
On the Evaluation of a State Power aimed at Preventing Urban Sprawl in Peri-Urban Areas of Chilean Cities. A Justification from Property Law
Keywords: Periurbanization
Property Law
Public Power
Sprawl
Urban Planning

In recent years, Chilean cities have experienced urban sprawl driven mainly by numerous residential projects located in rural areas close to the urban limits. This paper aims to evaluate one of the state powers that Chilean law offers to address this phenomenon. Since the exercise of such power implies a constraint on the property rights of the rural landowner, we will approach our study from Christopher Essert’s Property Law Theory complemented with a Kantian philosophical perspective. Under this conceptual framework, we will seek to justify the attribution of the Regional Agencies of the Ministry of Housing and Urbanism to prevent constructions and subdivisions in rural areas from generating new urban centers outside urban planning.
The Role of BLK in the Pathogenesis of Systemic Inflammatory Syndromes
Keywords: BLK
Immunology
Kawasaki Disease
Macrophages
Systemic Inflammatory Syndromes

Kawasaki disease (KD), systemic juvenile idiopathic arthritis (sJIA) and macrophage activation syndrome (MAS) share some clinical and pathobiological similarities. All three syndromes are accompanied by massive innate immune activation, similar pro-inflammatory cytokine signatures and successful clinical response to inhibition of shared cytokines. GWAS have identified that SNPs in BLK are linked to increased susceptibility in both KD and JIA. Common disease-associated SNPs are known to cause a 20-70% decrease in the expression of BLK, however, the association between the decrease in BLK and increased susceptibility in development KD is unknown. Using the LCWE induced coronary arteritis model of KD, we show that Blk-/- mice developed significantly larger coronary artery lesions compared to their WT counterparts evident by increased recruitment of inflammatory cells. Using bone marrow chimeras (BMCs), we demonstrate that the contribution of Blk in both stromal cells and immune cells is necessary for development of coronary inflammation in this disease model. Importantly, in KD patients, BLK gene expression is negatively correlated to circulating levels of IL-6, sIL-1R2, and sTNFR II. Furthermore, we found that the loss of Blk in mice has an important impact on monocytes and macrophages, evident by decreased percentage of CCR2+ monocytes within the bone marrow and macrophages within the peripheral blood at steady state. Blk-/- BMDMs have increased production and release of key pro-inflammatory cytokines including IL-6, TNFα, CXCL10, G-CSF, GM-CSF and CCL2 post-TLR2 stimulation. Furthermore, differential gene expression analysis demonstrated that the absence of Blk induced upregulation of ISGs in mice in accord with patient data showing that those with decreased BLK gene expression, have higher IFN responsive gene scores. Our results highlight the important role of BLK as a negative regulator of proinflammatory cytokine response in the pathogenesis of both mouse and human systemic inflammatory syndromes.
Trans Youth’s Family Lives Where Law Meets Science
Keywords: cisnormativity
medicalization
trans youth
transgender
transnormativity

This dissertation examines how Canadian courts deploy scientific authority as an epistemic and discursive resource to allocate power and shape the autonomy of trans youth within the family. To understand how courts use scientific authority, I draw on the conceptual tools of trans-affirmative scholarship—most notably the notions of cisnormativity and transnormativity—and on the sociological theory of medicalization. By carefully analyzing the case law on social gender affirmation and parental behaviour towards trans youth, I demonstrate that scientific authority acts as a double-edged sword in the legal lives of trans youths. On the one hand, scientific authority secures limited forms of social gender affirmation. On the other hand, judges’ deployment of scientific authority medicalizes transitude and expands the power of healthcare professional over trans youth’s lives. Having medicalized transitude, family law seeks less the self-determination of trans youth than their management. This dissertation contributes to the growing body of legal scholarship on trans youth by problematizing family law’s recourse to science and forging a path towards gender self-determination.
Decisional Needs of Parents of Children with Non-Ambulant Cerebral Palsy Recommended for Hip Reconstructive Surgery
Keywords: Cerebral Palsy
Decision-Making
Nursing
Paediatrics

Abstract Background: Cerebral palsy (CP) is a paediatric motor disability characterized by motor symptoms and hip displacement. Children with non-ambulant CP typically experience co-occurring comorbidities and higher incidences of hip displacement, which is associated with decreased quality of life (QOL). Treatment of hip displacement has focused on elective hip surgery with little evidence for optimal timing. Parents may struggle with the decision on when to proceed with hip surgery and may benefit from supports such as a decision aid. Purpose: To identify potentially relevant decision-aids and understand the decisional needs of parents who will make or have made a hip surgery decision for their child with non-ambulant CP including the level and associated factors of decisional conflict and regret. Method: A scoping review of decision-aids was followed by two studies conducted within an existing longitudinal study, CP Hip Outcomes Project (CHOP), that examines how surgical and non-surgical hip interventions affect health-related QOL in children with non-ambulant CP. Study 1 was a mixed methods study focused on decisional conflict in parents presented with the option of hip surgery and included a cross-sectional survey analyzed descriptively and interviews guided by Interpretive Description. Study 2 was a cross-sectional survey study where multiple linear regression was used to examine the level and predictors of decisional regret in parents of children with CP who had hip surgery. Results: The scoping review yielded no decision aids related to hip surgery. Of the 11 parent participants in Study 1, 36.4% reported clinically elevated levels of decisional conflict. In Study 2, 13 of 45 parent participants (28.9%) reported moderate to severe decisional regret, which was significantly predicted by lower levels of shared decision-making. Parents in Study 1 identified four key factors which supported their decision-making: Necessity of Surgery; Focus on Future QOL; Processing Time; and The Importance of Information. Conclusion: To reduce decisional conflict and regret related to hip surgery in parents of children with non-ambulant CP support should focus on engaging in shared decision-making, optimizing time for deliberation, and providing certainty around the trajectory of QOL. A decision aid may be an important tool for providing support.
Design, Characterization, and Performance of Adsorptive Membranes for Nutrient Recovery from Water
Keywords: Adsorption
Ammonium
Membrane fabrication
Nutrient recovery
Phosphorus
Wastewater treatment

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.
High Through-put Screening Studies of Intercellular Cell Interactions for Small Cell Clusters using a Microfluidic Device
Keywords: Cell culsters
Cell interactions
Hydrogels
Microfluidics
Raman scattering

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.
Analysis and Design of Distributed MIMO Wireless Networks
Keywords: Deep Reinforcement Learning
Distributed Antenna System
Machine Learning for Wireless Communications
Telecommunications
User-Centric Cell-Free Massive 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.
On Meeting a Maximum Delay Constraint Using Reinforcement Learning in Wireless Networks
Keywords: Max-delay Constraint
Monte Carlo Tree Search
Reinforcement Learning
Scheduling
Traffic Prediction

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.
The Effects of Automation Transparency on Human Performance
Keywords: automationtransparency
meta-analysis
transparency

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.