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Deliberative Machines: From Reflective Dialogue to Fair Consensus with Language Models and Social Choice
No full textThis thesis investigates the bidirectional relationship between artificial intelligence (AI), particularly large language models (LLMs), and social choice theory. Firstly, it explores how principles from social choice can address challenges in AI alignment, specifically the problem of aggregating diverse human preferences fairly when guiding AI behavior (SC → AI). Standard alignment methods often obscure value conflicts through implicit aggregation. Secondly, it examines how AI techniques can enhance collective decision-making processes traditionally studied in social choice (AI → SC), offering new ways to elicit and synthesize the complex, nuanced, and verbal preferences that conventional mechanisms struggle to handle.
To address these issues, this work presents computational methods operating at the interface of AI and social choice. First, it introduces Interactive-Reflective Dialogue Alignment (IRDA), a system using LLMs to guide users through reflective dialogues for preference elicitation. This process helps users construct and articulate their values concerning AI behavior, resulting in individualized reward models that capture preference diversity with improved accuracy and sample efficiency compared to non-reflective baselines, especially when values are heterogeneous.
Second, the thesis proposes a framework for generating fair consensus statements from multiple viewpoints by modeling text generation as a token-level Markov Decision Process (MDP). Within this MDP, agent preferences are represented by policies derived from their opinions. We develop mechanisms grounded in social choice: a stochastic policy maximizing proportional fairness (Nash Welfare) to achieve ex-ante fairness guarantees (1-core membership) for distributions over statements, and deterministic search algorithms (finite lookahead, beam search) maximizing egalitarian welfare for generating single statements. Experiments demonstrate that these search methods produce consensus statements with better worst-case agent alignment (lower Egalitarian Perplexity) than baseline approaches.
Together, these contributions offer principled methods for eliciting diverse, reflective preferences and synthesizing them into collective outputs fairly. The research provides tools and insights for developing AI systems and AI-assisted processes that are more sensitive to value pluralism
What’s In a Post? Adolescents’ Social Media Response Motivations, Perceptions of Response Motivations, and the Role of Individual Characteristics
No full textAs the questions of ‘why’ and ‘how’ adolescents use social media are more informative for understanding socio-emotional outcomes than the amount of time spent on social media, there have been recent calls for experimental studies of youths’ social media experiences. In the present studies, I examined what responses adolescents hoped to receive from others, and the degree to which other users could detect these wanted responses from their social media posts and the characteristics of youth associated with such motivations and perceptions. I further examined the themes, linguistic features, and emotional valence adolescents included in their social media content, and examined relations between the generated content and the characteristics of posters associated with motivations and perceptions. Adolescents (ages 13-16; N=103) participated in a simulated Instagram task where they created social media posts and indicated the degree to which they hoped to receive engagement, advice, support, or entertainment from others for each post, as well as the level of insight they felt they had into their own motivations. Adolescents reported wanting others to engage and be entertained more than they wanted to receive advice and support. Adolescents’ individual characteristics (i.e., social media use, peer relationships, empathy, mood, and emotion regulation) differentially related to what they hoped to receive from others. In a second phase, adolescents (ages 13-17; N = 88) viewed posts from others and rated what they felt the poster had hoped to receive. While the posters’ report and viewers’ ratings correlated, for all response options, adolescent viewers perceived that the poster wanted less of a response than the poster indicated wanting. In the content analysis (816 posts, N = 102), adolescents tended to create social media content that included little to no emotion words, disclosed very little/nothing to a moderate amount of personal information, was literal in its communicative intent, and tended to convey a congruent affect between caption and picture. These features suggest adolescents tend to create social media posts that are consistent with social media norms to avoid emotional posting or disclosing sensitive information to large online audiences. Adolescents’ individual characteristics (i.e., empathy, online and offline peer experiences, emotion regulation skills, mood, and social media use) were associated with their created social media content. Together findings highlight the variability in motivations for social media use based on adolescents’ characteristics and suggest a mismatch between motivations from posters and perceptions from online viewers. This work adds to a growing body of literature examining how adolescents navigate their complex, and increasingly online, communicative interactions
Analysis of the Three-operator Davis-Yin Splitting in the Inconsistent Case
No full textThis thesis analyzes the Davis–Yin three-operator splitting method in the inconsistent case, where the underlying monotone inclusion problem may fail to have a solution. The Davis–Yin algorithm extends the Douglas–Rachford and forward–backward splitting methods and is effective in reformulating optimization and inclusion problems as fixed-point iterations. Our study investigates its behavior when no fixed point exists. We prove, under mild assumptions, that the Davis–Yin shadow sequence converges to a solution of the normal problem, which represents a minimal perturbation of the original formulation
Electrochemical Modeling of Bioenergy Generation from Wastewater by Microbial Fuel Cells
No full textAs global water scarcity and environmental pollution continue to escalate, innovative wastewater treatment technologies are needed to ensure sustainable water resource management. Conventional wastewater treatment methods, such as activated sludge processes, are energy-intensive, costly, and contribute significantly to greenhouse gas emissions. Microbial fuel cells (MFCs) present a promising alternative, harnessing electroactive bacteria to simultaneously degrade organic pollutants and generate electricity. By leveraging microbial metabolism, MFCs can convert chemical energy in wastewater into usable electrical energy, offering a dual benefit of pollution reduction and renewable energy production.
This study focuses on developing a numerical simulation framework to optimize MFC performance, with an emphasis on real-world application at the Guelph Water Resource Recovery Centre (WRRC). A steady-state microbial fuel cell model was developed and validated using experimental data from previous studies. The model employs a finite difference method to solve mass balance equations for key reactants and products, including acetate, dissolved CO₂, protons, and oxygen. The simulation results highlight the influence of various operational parameters—such as substrate concentration, internal resistance, wastewater flow rate, and temperature—on the performance of a dual-chamber MFC. The study further compares MFC efficiency with conventional wastewater treatment processes, demonstrating a significantly higher chemical oxygen demand (COD) removal rate in MFCs (0.0633 kg COD/m³/day), which is approximately 4.7 times greater than that observed at the WRRC.
The results emphasize the role of microbial activity and electrochemical interactions in optimizing power generation and pollutant degradation. Key limitations such as oxygen transport restrictions, internal resistance, and pH imbalances were identified, suggesting areas for improvement in MFC design. Numerical simulations were further extended to model full-scale integration within WRRC, providing insights into the feasibility of MFC technology as an alternative treatment strategy. Despite challenges in large-scale deployment, MFCs show strong potential for reducing wastewater treatment energy demands and mitigating environmental impacts.
This research contributes to the advancement of MFC applications in wastewater treatment by demonstrating the effectiveness of numerical modeling in predicting and optimizing system performance
Fighting tuberculosis hand in hand: A call to engage communities affected by TB as essential partners in research
No full text© 2025 Venkatesan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Tuberculosis (TB) is an infectious disease closely intertwined with stigma, discrimination, and the social determinants of health. Communities of people affected by TV are experts in their care pathways, but the TB field continues to fall short of meaningfully engaging communities in TB research. This is a missed opportunity to improve the quality, relevance, person-centeredness, positive impact, and sustainability of TB research outputs. We acknowledge the important progress that has been made to date regarding community engagement in TB, but emphasize persisting barriers to meaningful engagement, and the urgent need for updated and comprehensive TB-specific standards for such engagement in research. We highlight that core components of these standards should include the mobilisation of communities affected by TB, ensuring appropriate remuneration, representation of priority groups, and the use of non-stigmatising language in the engagement process. In addition, to meaningfully incorporate the experiences and expertise of communities affected by TB, their engagement in the research process should occur as early as possible, ideally before research priorities and directions are set, and the scope of the research should encompass questions and outputs relevant to the community. Furhter, knowledge-sharing between researchers and the community should be ensured, not only of the research outputs but also regarding the engagement process itself, so that lessons learned can be carried forward. Lastly, the sustainability of community engagement processes (whether within institutions or projects) should be ensured, including through adequate funding for such engagement and the training, community mobilisation and relationship-building that this requires
Design of a Multi-Stage Power Amplifier for a 16 Element MIMO Transmitter Testbed
No full textThe next-generation standard for fifth-generation (5G) wireless communication demands significant advancements in the transmitter front end compared to its predecessor. This need arises from the exponential increase in both data rate requirements and the number of connected devices. The primary approach to achieving these improvements relies on the adoption of massive multiple-input multiple-output (mMIMO) systems. These systems, combined with beamforming technology, which enhances the equivalent isotropic radiated power (EIRP) by focusing transmission power in specific directions, increase the data rate of the communication systems.
While 5G aims to leverage millimeter-wave frequencies for increased bandwidth and data rates, the sub-6 GHz spectrum remains valuable, offering a practical balance between range and performance. Given the new performance requirements, the power amplifier (PA) must exhibit high linearity to minimize memory effects and distortion. As the most power-intensive component in the transmitter chain, the PA also faces increasing efficiency challenges, particularly due to the rising peak-to-average power ratio (PAPR) in 5G systems. In mMIMO configurations, additional complexities arise from factors such as load mismatch and antenna crosstalk, which further impact PA performance. Just as important, electromagnetic interference (EMI) within the transmission chain itself can degrade overall system efficiency —an often overlooked concern, which is the issue that this thesis addresses.
To address these challenges, this thesis presents a multi-stage Class AB PA operating in the 3.2–3.8 GHz range, designed for linearization within a 4×4 mMIMO transmitter array. External aluminum shielding is also employed to counteract the EMI. The PA is evaluated through S-parameter, continuous-wave (CW), and modulated signal simulations. CW simulations indicate that the driver and PA together achieve a small-signal gain of approximately 23–25 dB. The PA, utilizing 6W MACOM CGHV1F006 transistors, reaches saturation at 37 dBm output power. The 1 dB compression point is observed around 36 dBm, providing a broad linearity range before saturation.
The PA-stage demonstrates power-added efficiency (PAE) between 54% and 61% at maximum power, with a maximum phase distortion of -4 degrees at high-power levels. Modulated signal simulations, conducted with a 100 MHz modulation bandwidth, confirm that the PA is linearizable under single-input single-output (SISO) digital predistortion (DPD). The application of DPD reduces the adjacent channel power ratio (ACPR) from -35 dBc to -55 dBc, demonstrating a significant improvement in linearity compared to the non-DPD case
Rethinking Sustainable Tourism Certification: A Bottom-Up Evaluation of the Global Sustainable Tourism Council Framework as Measured by Certification Systems
No full textFor over 25 years, sustainable tourism certification, a market-driven mechanism designed to regulate production and consumption, has struggled to effectively serve small-scale ecolodges in the ecotourism sector. This challenge stems from certification programs failing to account for the operational realities and motivations of small business owners, leading to low adoption rates, impractical compliance expectations, and weakened trust in certification systems. The Global Sustainable Tourism Council (GSTC), the dominant authority in sustainable tourism certification, reinforces a top-down, universalist approach that limits flexibility and innovation. This study critically examines the GSTC system through a bottom-up framework that identifies sustainability practices more applicable to ecolodges, addressing the structural barriers embedded within certification. This research follows a three-step methodology to investigate the power dynamics, governance structures, and operational constraints of tourism certification.
Step 1 (Chapter 4) employs a descriptive analysis of industry reports, certification audits, and governance frameworks to assess how sustainability certification operates as an instrument of Private Environmental Governance (PEG) (RQ-1). By using Costa Rica’s tourism certification system as a case study, this step examines how organizations such as ISO, IEC, and ISEAL have influenced certification governance and credibility mechanisms. This global context highlights the GSTC’s regulatory dominance and the structural constraints it imposes on ecolodge certification.
Step 2 (Chapter 5) applies qualitative thematic analysis to expert interviews, synthesizing academic and industry perspectives on GSTC’s influence over certification management (RQ-2). The findings reveal that GSTC’s market control has led to monopolistic tendencies, positioning it as a de facto regulator in sustainable tourism governance. This study contributes to Monopoly Theory by demonstrating how GSTC exercises control over certification systems, reinforcing economic barriers and limiting competition in ecolodge sustainability models. The findings illustrate how PEG-driven certification, though intended to create market accountability, has instead produced unintended exclusionary consequences by prioritizing market influence over operational feasibility.
Step 3 (Chapter 6) builds on these findings to examine tourism experts’ assessments of GSTC’s criteria and the feasibility of ecolodge certification. This step integrates Club Theory
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perspectives to explore alternative ecolodge governance models (RQ-3), proposing a two-tier bottom-up framework to reduce certification hierarchy and increase accessibility for small-scale ecolodges. Tier 1 introduces 13 multi-dimensional indicators designed to ensure practical, transparent impact measurement for ecolodges with limited management scopes. Tier 2 integrates five adaptable sustainability components, addressing critical operational challenges for ecolodges with advanced management capacities. This tiered approach prioritizes transparency, accessibility, and regional flexibility, improving trust among ecolodges, customers, and regulators. While cost remains a major barrier to certification, this study demonstrates that ecolodges provide an opportunity for governance innovation, particularly for affordability-driven models.
By examining certification through the lens of PEG and Monopoly Theory, this research reveals that current governance models disproportionately serve large businesses while overlooking small, sustainability-driven enterprises. The findings suggest that adapting GSTC certification criteria to account for operational diversity is essential for developing a more effective, equitable certification model for tourism markets that prioritize sustainability and inclusivity
Bioderived Cyrene For Sustainably 3D Printing Organo/Hydrogels
No full textHydrogels possess unique properties that make them suitable for a wide range of applications. Recent advances in 3D printing techniques, such as stereolithography (SLA), have enabled the precise customization of hydrogel structures with complex geometries and controlled mechanical properties. Further development of advanced hydrogel properties remains a key research focus, with particular attention to improving properties such as mechanical integrity, electrical conductivity, and responsiveness to environmental stimuli. Strategies such as incorporating fillers and nanofillers into hydrogel matrices have been explored to enhance these properties. Additionally, the use of organic solvents instead of water, leading to the formation of organogels, has begun to expand the range of printable materials, addressing some limitations associated with hydrogel-based SLA printing, such as structural disintegration.
This thesis investigates the use of Cyrene, a bioderived and environmentally friendly solvent, as an alternative to traditional organic solvents in 3D-printed hydrogel systems. Organogels can be 3D printed, and afterwards a simple solvent exchange with water can convert organogels into the desired hydrogels materials, maintaining the advantage of biocompatibility along with the complex structures produced by SLA 3D printing. This research work started by exploring Cyrene’s role in hydrogel formulation, printability, and mechanical performance, comparing its effectiveness with the synthesis route using Cyrene and conventional solvents such as dimethyl sulfoxide (DMSO). Specifically, this study focuses on Cyrene’s application in mask stereolithography (mSLA) 3D printing of organogels. It demonstrates Cyrene’s excellent performance in enhancing hydrogel stretchability and swelling behavior after solvent exchange. Additionally, structural stability during organogel printing is improved due to the application of a previously developed acrylate salt. The findings reported in this work suggest that Cyrene-based hydrogels have promising applications in biomedical fields and soft robotics.
Furthermore, we extend this investigation by examining Cyrene as a dispersion medium for graphene, and its use in hydrogel nanocomposites. The study highlights Cyrene’s ability to stabilize graphene dispersion without the need for chemical surfactants, aiming to produce hydrogels with enhanced mechanical strength, electrical conductivity, and multifunctional properties. These advancements open new investigations for applications in flexible electronics, biosensing, and tissue engineering.
The research findings provide a comprehensive understanding of Cyrene’s potential as a sustainable solvent in the synthesis of organogels that can be converted into hydrogels after solvent exchange and used for a wide range of applications. The insights gained from this research contribute to the advancement of high-performance, eco-friendly hydrogel materials by demonstrating how Cyrene can serve as a sustainable alternative to conventional organic solvents. By utilizing a bioderived solvent to create organogels, followed by solvent exchange with water, the mechanical properties, structural stability, and biocompatibility of 3D-printed hydrogels can be enhanced. Additionally, the ability to stabilize graphene dispersion in hydrogels without chemical surfactants opens new opportunities for developing conductive and multifunctional hydrogel-based devices. These findings not only support the ongoing shift toward greener material synthesis but also lay the foundation for future innovations in sustainable material science and additive manufacturing
Investigating Abundances in Galaxy Clusters and Gas Motions in M87 using XRISM
No full textGalaxy clusters are the forefront of extragalactic diffuse X-ray astrophysics, yet there
are still many questions about their formation and evolution. The creation of XRISM,
a new X-ray imaging and spectroscopy mission, will study the metal abundance history
of clusters and the conversion of jet energy into atmospheric kinetic energy. XRISM’s
payload contains an instrument with the highest spectral resolution (5 eV) in the field
of X-ray astronomy so far. With this resolution, we observed metal abundances and the
broadening of metal lines through turbulent motions in the intracluster medium.
In this thesis I present the conversion of data from the Chandra X-ray Observatory to
XRISM’s high-resolution format. This includes the preparation and selection of clusters in
Chandra, simulating selected clusters for XRISM and applying for proposals. Finally, we
extracted abundance and velocity information from the Virgo cluster’s early XRISM data
Assembling Memories: A Concept of the Architectural Worldmaking of Memories in the Metaverse
No full textThis thesis explores the relationship between architecture and memory by investigating the use of immersive virtual environments (Metaverse), for recording and sharing memories by transforming personal experiences into collective architectural elements. Utilizing geolocation and augmented reality (AR) technologies, individuals document their memories of urban spaces through TikTok, which are then analyzed to extract significant characteristics to be transformed into architectural components. These digital representations are aggregated into a virtual collective memory world.
Taking Japanese Village Plaza in Little Tokyo, Los Angeles as a testing ground, this thesis proposes a design concept for an architectural memory assembly interface within the Metaverse. Through virtual overlays, users engage with these spaces, creating a more immersive, dynamic, and collaborative memory experience compared to traditional preservation methods. The thesis outlines a framework for utilizing these technologies to develop a shared, evolving memory world, where users co-create spatial experiences that merge personal and collective memories in the Metaverse