About MacSphere

MacSphere is McMaster University's Institutional Repository (IR). The purpose of an IR is to bring together all of a University's research under one umbrella, with an aim to preserve and provide access to that research. The research and scholarly output included in MacSphere has been selected and deposited by the individual university departments and centres on campus.

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Recent Submissions

MULTIPLE-TIME-SLOT COMMUNICATION RESOURCE ALLOCATION FOR MULTIPLE ACCESS COMPUTATION OFFLOADING
(2026) Liu, Xiaomeng
The Mobile Edge Computing (MEC) framework has been proposed as a means to address the demand for extending the computational capabilities of small-scale mobile devices, especially in scenarios with tight latency requirements, or devices with limited available energy. This framework enables devices to offload computational tasks to their network access point. When multiple devices seek to offload computational tasks to their access point, the nature of the multiple access scheme plays a critical role in the system performance. The main focus of this thesis is to optimize the allocation of the available communication resources among the offloading devices, so as to minimize a weighted sum of their energy consumption. To effectively allocate the available communication resources, we adopt a multiple-time-slot (MTS) signalling architecture in which different numbers of devices transmit in each slot, according to a chosen multiple access scheme. We consider a common orthogonal multiple access scheme, namely time-division multiple access (TDMA), and various classes of non-orthogonal multiple access (NOMA), including NOMA with independent decoding(ID), NOMA with fixed-order sequential decoding (FOSD), and the “rate-region-optimal” NOMA scheme that is able to achieve any point in the capacity region. The problem is formulated as an optimization problem that involves jointly selecting the devices that will offload, along with optimizing the communication resources, namely the power and rate of each device in each time slot, and the time slot lengths. The solution strategy for this problem is to embed the resource allocation problem within a customized tree search algorithm, for the binary offloading decisions. The thesis firstly explores the case in which the devices and access point are equipped with a single antenna. We show that the communication resource allocation problems for TDMA and the “rate-region-optimal” multiple access can be formulated as reduced-dimension convex optimizations. For NOMA with ID or FOSD, we show that the resource allocation problem has a difference-of-convex structure and we develop a successive convex approximation (SCA) algorithm with feasible point pursuit. Furthermore, for the FOSD scheme we obtain a closed-form expression that provides the optimal decoding order when it is feasible, and efficient algorithms for finding a good decoding order when it is not. In the next step, we explore the case in which the devices and access point are equipped with multiple antennas. For the “rate-region-optimal” multiple access scheme, we show that the communication resource allocation problem can be formulated as a reduced-dimension convex optimization problem. For TDMA, we determine feasibility using the principles of waterfilling, and develop an iterative algorithm based on successive convex approximation (SCA) for feasible cases. For NOMA with ID or FOSD, we show that the resource allocation problem has a difference-of-convex structure and we develop an SCA algorithm with feasible point pursuit. Furthermore, for the FOSD scheme we develop an efficient algorithm for finding a good decoding order that often achieves the same performance as the “rate-region-optimal” multiple access. Our numerical results provide insight into tradeoffs between the complexity of a multiple access scheme (and its resource allocation algorithm), and its performance in computation offloading. Finally, the thesis explores the communication resource allocation problem in computation offloading from an information theoretic perspective. To gain insight into how the choice of the multiple access scheme impacts the feasibility of offloading, we determine the regions of achievable average rates. These regions highlight the role played by the particular form of time sharing enabled by our MTS signalling architecture. To gain insight into the devices’ energy consumption, we consider the region of achievable energies, the boundary of which contains the set of Pareto optimal points for the minimum energy computation offloading problem. This region intuitively illustrates the scenarios in which suboptimal multiple access schemes can achieve the same energy consumption as the “rate-region-optimal” schemes and the gap between them when that is not the case. In particular, it inspires us to prove, analytically, that when the channel gains of the devices are equal, and their energy prices are equal, the minimum possible energy consumption over all multiple access schemes can be achieved using TDMA.
Mindfulness-Based Interventions for Older Adults: A Mixed-Methods Investigation
(2026) DeMaio, Peter; Andrews, Gavin; Health and Aging
Background: Older adults engage in mindfulness practices and programs to support their mental health, overall wellbeing, and age-related challenges. While existing research on mindfulness-based interventions (MBIs) are promising, evidence about their effectiveness, underlying mechanisms, and nuances about for whom and under what circumstances MBIs are more likely to work are limited. Aims: This PhD thesis provides a multidimensional examination of mindfulness in later life by exploring i) how older adults practice and perceive mindfulness in everyday life (Chapter 2), ii) the potential mechanisms and context-mechanism-outcome configurations that shape the effectiveness of MBIs (Chapter 3), and iii) the overall effectiveness of MBIs in older adults (Chapter 4). Methods: Three interrelated studies were conducted through a critical realist lens. First, a qualitative thematic analysis using in-depth interviews with older adults explored everyday mindfulness practices in everyday life. Second, a realist synthesis consisting of a systematic review and qualitative interviews with MBI instructors and older participants identified key CMO configurations. Third, a systematic review and multi-level meta-analysis of randomized controlled trials assessed the effects of MBIs on depression, anxiety, cognition, sleep, and pain in adults aged 60 and older. Results: Study one (Chapter 2) identified six core themes that collectively suggest that participants understand their mindfulness practice as a continuously evolving process that can be adapted in response to their needs, preferences and personal routines, and that mindfulness can provide benefits at individual, interpersonal, and societal levels. Study two (Chapter 3) identified six contexts, eight mechanisms, and six outcome groups, highlighting that certain mechanisms may work synergistically and be more important for certain older adults than others. Study 3 (Chapter 4) showed medium to large pooled effect sizes on depression and anxiety, and small effects on cognition and sleep. However, results were greatly limited by small sample sizes, large confidence intervals, and overall low-quality GRADE evidence ratings, highlighting the need for larger studies and better reporting practices. Discussion: Overall, the studies collectively showcase the potential of MBIs to address a range of challenges in later life when participant needs and preferences are matched with appropriate program delivery. The success of MBIs appears not only to rely on its content, but also the relational and processual aspects like instructor facilitation style and group dynamics and support. Larger, more robust, and better reported realist-informed studies are needed to examine how participant characteristics and contexts can be accounted for in MBI delivery to better leverage the key mechanisms that lead to improved outcomes. More research is also needed to clarify the mechanisms through which MBIs work, and how older adults can be supported to continuously practice mindfulness after MBI completion. These future efforts require interdisciplinary and mixed-methods research that can be supported by critical realism as a meta-theoretical framework. These insights will have important policy and practice implications to enable local, provincial/territorial, and national level governments in Canada to better support healthy aging.
Machine Learning-Enabled Droplet Microfluidics Reveals Functional Heterogeneity in NK Cell Immunotherapy
(2025-12-04) Ozcan, Rana; Vahedi, Fatemeh; Namakian, Shina; Ashkar, Ali; Didar, Tohid
Natural Killer (NK) cell immunotherapy faces challenges in predicting therapeutic efficacy due to functional heterogeneity within NK populations and tumor microenvironment (TME) suppression. Here, a droplet microfluidic platform enables automated single-cell analysis of NK cell-mediated cytotoxicity against cancer cells. A machine learning-based object detection model identified target cells and death events across image sequences and generated readouts. Distinct NK cells are evaluated to quantify key metrics, including the percentage of cytotoxic NK cells, serial killing capacity, killing time per target and NK-target attachment dynamics. The results demonstrated that expanded NK cells (exNK) exhibited superior cytotoxic activity, serial killing, and rapid killing dynamics, whereas peripheral blood NK cells (pbNK), especially when they were exposed to ascites TME (pbNK-asc), displayed reduced cytotoxic abilities in all parameters. Interestingly, expanded NK cells exposed to ascites TME (exNK-asc) retained partial functionality, indicating that expansion provides resilience against suppressive factors. This single-cell analysis provides novel insights into NK-cancer cell interactions, offering a robust framework for enhancing the efficacy of future immunotherapy applications especially for optimizing off-the-shelf NK cell-based immunotherapies.
Meeting Package: December 2025 Graduate Council
(2025) School of Graduate Studies
Approved Minutes: October 2025 Graduate Council
(2025) School of Graduate Studies

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