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Advances In FIB-SEM Nanotomography of Hard/Soft Biological Systems
No full textFIB-SEM nanotomography is a powerful 3D nanoscale characterization tool that performs iterative ion milling and electron imaging to produce high-resolution and large volume imaging. However, for biological samples, FIB-SEM nanotomography requires development and optimization to mitigate artifacts, drift and misalignments to ensure accurate volumetric data acquisitions. The research within this thesis seeks to optimize, analyze and evaluate the use of FIB-SEM nanotomography in biological systems consisting of bone, fossilized bone and bone cells. Bone tissue has a hierarchical organization with distinct hard and soft components at the macro- to nanoscale level. The fundamental nanoscale features of bone, mineral ellipsoids and collagen fibrils constitute the building blocks of bone, and how these components organize and change during external processes, including fossilization, is of high interest. FIB-SEM was optimized to visualize the organization of ellipsoidal mineral clusters and collagen fibrils within highly mineralized human bone tissue, where the twisted plywood organization of mineral ellipsoids was unveiled. Similarly, fossilized Albertosaurus sarcophagus bone tissue was imaged using FIB-SEM to analyze the microstructural organization of the bone, which revealed preserved mineral and organic fundamental components but also diagenetic changes in the specimen. Lastly, FIB-SEM was evaluated with a created semiconductor and Saos-2 (osteosarcoma) cell sample. Through post-acquisition analysis, deviations and errors were identified and corrected, thereby providing a customizable and biologically relevant standard that can be used for 3D FIB-SEM data validation. This thesis advances the utilization of FIB-SEM nanotomography as a reliable nanoscale characterization tool for bone imaging by providing in-depth details on the structural organization of key bone components and insight into the FIB-SEM acquisition behaviour during biological acquisitions. These insights advance the broader bioimaging field, where enhanced nanometer-scale 3D imaging over large volumes provides greater understanding of biological building blocks
Semi-Markov Multi-State Models for Cardiovascular Outcomes: Beyond Composite Time-to-First Endpoints
No full textIn cardiovascular trials, composite endpoints are typically analysed with time-to-first (TTF) methods. The composite endpoints under TTF ignore subsequent events and associations with different event types, which can overlook disease burden and treatment benefit. This thesis proposes a Multi-state Model (MSM) as an alternative for cardiovascular trials, providing detailed insights into transitions among states representing different types of disease. We develop three semi-Markov MSM structures from the cardiovascular composite used in the ORIGIN (Outcome Reduction with an Initial Glargine Intervention) trial: 3-state illness–death model, 5-state irreversible model, and 5-state reversible model. We then conduct Monte Carlo simulations to compare MSMs with TTF Cox models in terms of Type I error, power, confidence interval width, and hazard ratio estimation. In the simulation, we demonstrate the ability to detect a treatment effect among intermediate states while maintaining a 5% Type I error rate for other states showing no effect. In contrast, none of the TTF estimates detect any treatment effect. As more states and transitions are added, the precision of the estimates and the power to detect any treatment effect for subsequent transitions become increasingly limited by the availability of events. We apply these MSMs to ORIGIN to re-analyse cardiovascular outcomes between the treatment groups. Key outputs include the treatment effect for each transition, cumulative incidence, state occupation probabilities over the follow-up period, and the restricted mean time spent in each state, providing insights beyond TTF analysis. Semi-Markov MSMs complement traditional TTF analyses by decomposing composite endpoints into clinically interpretable transitions in cardiovascular trials. This is particularly useful in studies with higher rates of non-fatal events allowing for deeper exploration of disease burden from subsequent transitions
MASK-FREE SHADOW REMOVAL VIA FREQUENCY DISCRIMINATION AND FOUNDATION MODEL FUSION
No full textShadow Removal is a significant topic in image restoration, which in recent
years has seen vast progress thanks to the wide application of deep learning on image
processing. However, many of the shadow removal methods nowadays relies on the ex istance of masks during training phase, which adds to the human resources needed to
annotate shadows and limit the dataset availability. In this thesis, we propose a novel
mask-free shadow removal framework utilizing both Vision Transformer and CNN based network. Specifically, a foundation model based on ConvNextV2 network learns
the local texture, restores realistic lightning and a tweaked Vision Transformer called
FFTFormer removes global shadow artifacts by separating it based on Fast Fourier
Transform(FFT) . In addition, we conducted detailed ablation study experiments by
replacing modules and comparing the different metric results, both statistically and
graphically
Mindfulness-Based Interventions for Older Adults: A Mixed-Methods Investigation
No full textBackground: 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.ThesisDoctor of Philosophy (PhD)Mindfulness might help older adults improve wellbeing, adapt to age-related changes, and manage stress, but research has not fully explained how and for whom mindfulness-based programs work best. This PhD thesis examined mindfulness in later life through three related studies. The first explored how older adults understand and practice mindfulness in their day-to-day life. The second combined a literature review and interviews with mindfulness instructors and older participants to understand how mindfulness-based programs might work. The third combined results from clinical trials to see how effective these programs are for depression, anxiety, cognition, sleep, and pain in adults aged 60 and older. Overall, the findings suggest that mindfulness can improve emotional wellbeing and social connection, especially when programs are adapted to participants’ individual needs. The research highlights the need for larger, more rigorous studies and offers insights for designing programs and policies to support mindfulness programs for older adults
MULTIPLE-TIME-SLOT COMMUNICATION RESOURCE ALLOCATION FOR MULTIPLE ACCESS COMPUTATION OFFLOADING
No full textThe 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
The paradox of prosperity: Why higher earnings can reduce growth aspirations
No full textThis study fills a key gap by showing that entrepreneurial growth intentions are not static, but rather shaped by prior success and recent constraints, challenging the assumption that higher income always signals future expansion. Using survey data from Canadian small firms, this study finds that financial and human resource barriers spur growth ambitions, while regulatory and competitive pressures dampen them. This dynamic perspective advances understanding of how past performance and contextual obstacles interact, offering insights for policymakers and lenders to better forecast growth potential and tailor support strategies beyond simple financial indicators
PRIORITIZATION IN MEDICAL HUMANITARIAN AID: A BRIEF LOOK INTO THE FUNDAMENTAL PRINCIPLES
Full text linkN/AUnited Nations and partner organizations assisted almost 200 million people in 2022 across 63 countries through joint funding amounting to 41 billion dollars (United Nations Global Humanitarian Overview, 2022). Some organizations taking on the biggest burden of providing this aid, specifically medical humanitarian aid, are the International Committee of the Red Cross and Médecins Sans Frontières. In 2023, these organizations addressed almost 200 missions worldwide, staffing nearly 100,000 across both organizations (ICRC, Annual Report 2023) (MSF, Annual Report, 2023). As the number of people requiring aid globally continues to increase while funding and capacity dwindle, a resource allocation crisis is created, forcing these organizations to prioritize (Slim, 2024). Priortization, a more contemporary term in humanitarian aid is understood as who humanitarian aid organizations can help and when. The ICRC and MSF maintain clear ethical codes, such as the ICRC’s list of Fundamental Principles, however, the justifications that humanitarian aid organizations articulate for prioritization are vaguely externalized. Therefore, The research question guiding this paper was, “How do humanitarian aid organizations (e.g., IRC and MSF) articulate justifications for prioritization?” The initial literature review revealed that humanitarian aid organizations partly derive decision-making processes from certain internal ethical codes and principles, whether implicitly or explicitly. This prompted a realist evaluation of three emergency humanitarian interventions as case studies, a conflict, climate, and epidemic disaster through publicly available data. The cross-analysis of those three case studies, the Syrian Civil War (2011-ongoing), Cyclone Idai (2019), and finally the Ebola Virus Outbreak in West Africa (2014-2016) indicated the absence of some principles and the presence of other external factors that influence prioritization.ThesisMaster of Health Sciences (MSc)1 in 22 people globally require humanitarian aid, totaling an “all-time high” of 362 million in 2024 (UNIS, 2024). As humanitarian aid organizations struggle to address rising needs, brief insights into the future reveal that prioritization, who and when humanitarian aid organizations choose to help will soon become a necessary protocol (Slim, 2024). How organizations currently engage in articulating justifications for prioritization is unclear. Therefore, this paper's research question is “How do humanitarian aid organizations (e.g., IRC and MSF) articulate justifications for prioritization?” The literature search revealed that humanitarian aid organizations partly derive decision-making processes from internal ethical codes and principles, directing the study to assess through a realist evaluation, the presence of the fundamental principles as justifications for prioritization across three different case studies of humanitarian interventions. This revealed the presence of some principles, the absence of others, and the influence of external factors
Phenotypic Measures of Stemness for Discovery of Novel Therapeutic Targets and Personalized Medicine
No full textHealthy stem cells are rare, long-lived cells with unlimited self-renewal potential, enabling organ regeneration. Similarly, cancer stem cells (CSCs) contribute to cancer initiation, post-chemotherapy regeneration and development of drug resistance through their stemness properties of self-renewal highlighting them as a key therapeutic target in relapse prevention. Relapse and drug resistance represent the two biggest clinical hurdles to improving patient outcomes. Since CSCs are rare and governed by different cellular pathways than the bulk of the tumour they require unique ways of targeting. However, CSCs are difficult to isolate and study. CSCs, like all stem cells, are only defined by functional (aka phenotypic) assays that measure self-renewal and differentiation. My research aims to utilize phenotypic measures of stemness to address these clinical hurdles in therapy. First, I conduct a meta-analysis to highlight the importance of phenotypic assays in drug discovery compared to targeted base approaches. This meta-analysis reveals that drugs discovered using phenotypic assays were more likely to be approved for clinical use and less likely to fail due to lack of efficacy. Based on these results I proceed in two directions: using phenotypic measures of stemness for new drug discovery and using it for personalized medicine to improve already clinically approved therapies. First, using a phenotypic chemical genomics approach I uncover a novel vulnerability of CSCs through the targeting of SARNP and the transcription and export (TREX) pathway. This work uncovers a novel role for SARNP in R-loop homeostasis and importantly identified TREX as a targetable pathway for cancer stem cell drug discovery. Secondly, I develop a novel personalized medicine platform that integrates functional measurements of stemness, quantitative drug profiling and genetics which clinicians can use in real-time to improve therapy choices. Importantly, this platform can predict patient response to chemotherapy with 90% accuracy and identify clonal populations that are drug-resistant and relapse-driving leading to refractory disease. Overall, my work highlights the importance of phenotypic approaches to stem cell biology for personalized medicine and cancer drug discovery.DissertationDoctor of Philosophy (PhD)Healthy stem cells are rare cells that can divide indefinitely and turn into other types of cells through a process called differentiation. This process is crucial for the regeneration of our tissues throughout our lives. However, when they acquire mutations healthy stem cells turn into cancer stem cells which are responsible for the initiation and regeneration of cancer leading to relapse. It is believed that release can be prevented if cancer stem cells are irradicated. Cancer stem cells are challenging to target because they are rare, distinct from the bulk of the tumor, and share many characteristics with healthy stem cells. Effective therapies must specifically eliminate CSCs without harming healthy stem cells, which are vital for tissue regeneration. Unfortunately, the development of such therapies is hindered by our limited understanding of the key differences between CSCs and healthy stem cells. To address this, my thesis uses advanced models of stem cells to identify critical distinctions between cancerous and healthy stem cells. By uncovering these differences, my goal is to develop drugs that can precisely target CSCs, improving cancer treatments while preserving healthy tissues
Community and Sanctuary within the Chora of Metaponto
No full textThe following thesis investigates routes of communication and connectivity within the chora of Metaponto. Using digital methodologies within a project Geographic Information System, Least Cost Path (LCP) is used to reconstruct ancient routes between rural farmsteads and sanctuaries. LCPs are a means of presenting lines drawn over digitized terrain in order to reconstruct the easiest route of travel between two points with respect to cost factors such as slope and distance. The results of Least Cost Path are then compared against topographical anomalies identified within the landscape of the chora, many of which confirm the likelihood that these linear anomalies were used as ancient routes of travel. A survey of ancient scholarship regarding the parceling of land in both colonial and rural contexts suggests that the lines identified in the chora and supported by this LCP analysis are evidence of rural land division, urban planning, and of ancient roads from as early as the 6th century BCE.
This evidence is used to suggest that independent communities formed within the Metapontine chora, using rural sanctuaries as locations for agglomeration in both cultic and secular contexts. The founding of these sanctuaries created spheres of influence within which a nucleated collection of inhabitants of the countryside formed. The boundaries of these rural communities are identifiable using a combination of Cost-Distance Allocation and a system of land division first proposed by Giovanni Uggeri in 1969.
This thesis concludes that communities formed within the chora of Metaponto, exercising self-governance in local affairs related to life in the countryside. Identities within these communities were of a composite nature, at once both members of a polis and of a unique regional community centered upon their nearest extra-urban sanctuary. Residents of the chora used these sacred spaces as the symbolic capitol of their neighbourhood and the sanctuaries themselves communicated the limits of Metapontine influence and protection.ThesisDoctor of Philosophy (PhD)This thesis investigates the nature of rural habitation and use of sacred spaces in the countryside of the Greek settlement of Metaponto. Using digital methodologies within the field of landscape archaeology and a robust database of archaeological material, routes of access are reconstructed between these rural settlements and their nearest sanctuary beyond the walls of the city proper. When visualizing these routes which have been digitally reconstructed, it becomes clear that they meaningfully interact with linear topographical anomalies identifiable in the landscape of the countryside. This provides confirmation of the use of these routes in antiquity, as well as of regular frequentation at these sacred sites. These data are then used to explore autonomy outside the city of Metaponto and to suggest that regions formed in which sacred spaces were used as points of contact among residents of the countryside, creating communities which self-managed and evolved semi-independently from the asty
A Spectroscopic Framework for Deriving Elemental Abundances of M Dwarfs
Full text linkMeasuring accurate stellar abundances of planet-forming elements is critical to our understanding of exoplanet compositions and their formation processes. While these values can be reliably derived from optical spectra for FGK-type stars, the recovery of accurate abundances for M dwarfs is complicated due to persistent discrepancies between models and observed spectra, such as blended absorption features and broad molecular bands that obscure the continuum. These lingering uncertainties in M dwarf chemical compositions inhibit our ability to accurately model the interiors and atmospheres of exoplanets around M dwarfs. To address this issue, we have built a custom framework to extract elemental abundances from the spectra of cool stars via the spectral synthesis method. We showcase our methodology as well as the derived elemental abundances for a pair of cool stars. SPIRou, with its high spectral resolution and broad near-IR wavelength range, is the ideal instrument to help mitigate the difficulties present in the recovery of M dwarf elemental abundances. By combining the capabilities of SPIRou with our framework, we are well equipped to ensure the accuracy of derived elemental abundances in M dwarfs. Our results will ultimately be applied to planet-hosting M dwarfs in order to place strong constraints on the planets’ refractory and volatile abundances, both of which are important diagnostics of planetary formation histories and interior compositions.ThesisMaster of Science (MSc)Understanding what planets are made of helps us learn how they form. Since planets and their stars are created from the same materials, we can study a star’s composition to learn more about the planets that orbit it. Measuring the abundances of planet-forming elements like magnesium, silicon, and iron is routinely performed for Sun-like stars, but the task proves to be much more difficult for smaller, cooler stars like M dwarfs. M dwarfs are very common and host most of the super-Earths within the Milky Way that could potentially support life, so studying them is crucial. My Master’s thesis focuses on developing a method to accurately measure the elemental abundances in M dwarfs using high-resolution spectra taken at infrared wavelengths where M dwarfs emit most of their light. My work is helping to improve our understanding of the composition and formation pathways of exoplanets around M dwarfs