30921 research outputs found
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Creative management as a design tool for biodiversity
No full textLandscape management plays a key role in the appearance and use of designed landscapes over time. It is typical for management plans to be a last consideration, something that comes at the tail end of the design process or is not considered part of the design process at all. If they are part of the process these plans tend to work against natural successional patterns with the goal of maintaining the visual aesthetic of the original design over a number of years. But what if management was used as the primary tool for design to work alongside and encourage certain successional patterns that enhance biodiversity to create dynamic landscapes over time? In my practicum, I will explore how creative management of vegetation in a local golf course in Winnipeg, MB Canada allows for increased biodiversity and successional patterns.
Contrary to regular approach to landscape maintenance, creative management is an adaptive approach that responds to on the ground conditions in the moment. This requires an in-depth understanding of the site through various times and seasons to experience the patchwork of micro conditions that make up a landscape. Once people are equipped with the knowledge of the land it enables them to respond quickly and appropriately to changes in the land in order to benefit the habitats as a whole.
I have identified a number of habitat types and will develop a management plan for each one. This practicum will take two golf courses and transform them into a mosaic of different habitats with the goal of creating and enhancing biodiversity within the city. In order for creative management to support biodiversity it has to be intentional with its timing and methods. For this reason I have selected a number of endangered insects and animals to create specific habitat for which will provide a base for the project. The Manitoba list of species at risk informed the selection of species to create and manage habitat for. From an in-depth study of the life cycles of the selected species along with real life experience in the field of landscape management a series of strategies were developed that will be used to transform the golf courses into prime habitat. Homogeneous lawns will become large fields of prairie and wet meadow. Retention ponds and other low areas will become a patchwork of pothole prairie marshes scattered across the landscape and the creation of a dune field will provide a unique habitat within the city.October 202
Three Homeric Descripta from Karanis
No full textPublication of three previously described Homeric papyri, all from the village Karanis. Archaeological and archival data is brought to bear on the histories of each papyrus
Evaluating physiological coherence of microvascular hemodynamics between brain and skeletal muscle using high-resolution near-infrared spectroscopy
No full textPhysiological coherence between organ-specific microvascular hemodynamics is a fundamental yet underexplored aspect of human systemic blood flow regulation, particularly in systemic vascular diseases such as critical illness. Current critical care monitoring predominantly relies on systemic macro-hemodynamic parameters, which fail to capture the heterogeneity and dynamic relationships of microvascular perfusion across organs like brain and skeletal muscle. This knowledge gap is especially evident regarding the temporal and frequency-specific coherence of microvascular signals between these organs, limiting the development of targeted, organ-specific therapies. To address this, we developed a novel methodological framework to quantify physiological coherence between brain and skeletal muscle microcirculation using high-resolution Near-Infrared Spectroscopy (hr-NIRS) and advanced wavelet-based signal processing. This study employed continuous, non-invasive monitoring in ICU patients (n=40) and healthy controls (n=15), simultaneously acquiring total hemoglobin (HbT) from the frontal cortex and brachioradialis, along with systemic blood pressure. Time-frequency and time-phasic relationships were characterized using wavelet coherence and semblance analyses, assessing both the strength and synchrony of microvascular coupling across cardiac and microvascular frequency bands. Key findings include: (i) ICU patients exhibited significantly reduced coherence duration and phase synchrony between brain and skeletal muscle microcirculation in the cardiac frequency band compared to healthy controls; (ii) ICU non-survivors demonstrated excessive synchronization between skeletal muscle microcirculation and systemic blood pressure in the microvascular and cardiac frequency bands compared to ICU survivors. These results establish, for the first time, that dynamic physiological coherence between brain and skeletal muscle microcirculation is significantly altered in critical illness, with distinct patterns associated with patient outcomes. Integrating wavelet-based coherence metrics into bedside monitoring offers a promising direction for the development of novel biomarkers to guide personalized therapeutic strategies and risk stratification in the ICU.University of Manitoba Graduate Fellowship (UMGF) - 2024October 202
Orderability, generalized torsion and amalgams
No full textWe study two related topics about orderable groups. First, we investigate a type of order-preserving isomorphism of free groups to study the bi-orderability of group extensions. We give a sufficient condition ensuring these isomorphisms are order-preserving. As an application, we answer a question of Kin and Rolfsen affirmatively. Second, we study generalized torsion elements in amalgams of groups. Our main theorem gives a sufficient condition ensuring an amalgam to be free of generalized torsion. As an application of the main theorem, we construct groups that are generalized torsion free and not left-orderable, solving problem 16.48 (on Page 98) of The Kourovka Notebook.October 202
A study of extrusion printed millimetre-scale MEMS transducers
No full textThis thesis presents a comparison in performance of various microelectromechanical devices fabricated by both lithographic methods in a clean room facility and by means of extrusion printing of conductive ink. Traditional microelectromechanical systems (MEMS) fabrication practices involve costly, time-consuming and complex multi-step processes utilising high-end, high-maintenance cleanroom facilities. On the other hand, printed electronics (PE) offers quick turn-around time, low-cost, and simplicity.
The work completed in this thesis involves taking candidate MEMS transducer designs intended for clean room fabrication and scaling them up to the resolution of a direct-ink write extrusion printer. Firstly, unknown ink parameters are determined through experimentation and simulation. Then, past MEMS designs for a Lorentz actuator and DC electric field sensor are scaled up and in some cases changed slightly to accommodate PE. A Lorentz actuator-based electromagnetic relay is designed as well. The devices are then fabricated using a direct ink writing (DIW) printer in conjunction with a laser micro-machining tool, and are tested to both verify the simulations and offer comparison to their respective MEMS counterparts and/or other similar devices from the literature.
A key finding was comparable performance metrics between the PE devices fabricated in this thesis, and their respective lithographic or commercially available counterparts. This signifies that PE is a viable alternative to lithography for manufacturing some MEMS devices, or at least offers itself as a means of rapid prototyping. In addition, the ink used in this thesis was characterized for use in simulation models.October 202
The role of SRP9/SRP14 in regulating Alu RNA
No full textThere are over 1 million Alu elements in the human genome which have the potential to be transcribed into discrete, non-coding Alu RNAs. Alu RNAs are involved in a myriad of biological diseases and are thought to interact with the protein heterodimer SRP9/SRP14. Although 99% of Alu RNAs are unique, most research has been focused on the signal recognition particle RNA and its interaction with SRP9/SRP14. In this project, SRP9/SRP14 is established as a transcriptional regulator of both the signal recognition particle RNA, and another abundant Alu RNA, brain cytoplasmic RNA 1 (BC200). In this study, the association of SRP9/SRP14 to the Alu genetic loci was observed independently of transcription, and a model of SRP9/SRP14 co-transcriptionally regulating Alu RNA was proposed. Following this, minor mutations to the BC200 Alu domain were revealed to significantly decrease expression. Structural characterization and modelling of the BC200 Alu domain and the low expression mutant demonstrated both RNA possess canonical Alu RNA fold. A recently discovered short human Alu RNA was found to have a unique Alu RNA fold and lacked association with SRP9/SRP14. Ribonucleoprotein immunoprecipitation followed by sequencing of SRP9 and SRP14 was also used to identify 21 novel non-coding Alu RNA. Together, this project demonstrated the significance of SRP9/SRP14 in modulating Alu RNA expression, while highlighting the structural diversity and sequence variability of Alu RNA.Natural Sciences and Engineering Research Council of Canada - CGS-D
Natural Sciences and Engineering Research Council of Canada - CGS-MOctober 202
Self-compassion and risk-taking in sport injury rehabilitation
No full textSelf-compassion, a state characterized by treating oneself with kindness, recognition of common humanity, and mindful awareness of suffering, is an asset in coping with the challenges presented by sport injuries. However, it is not yet known how self-compassion may affect the ways in which athletes approach rehabilitation decisions. Previous literature suggests self-compassion may influence decision-making by either: i) encouraging self-protection, or ii) encouraging authentic expression of preferences and personality. The purpose of this dissertation was to examine whether self-compassion promotes one of these perspectives and how this influences risk-taking in rehabilitation decisions.
This dissertation consists of two studies, both surveying university undergraduates who participate in sports. Participants were presented with a hypothetical sport injury scenario and prompted to describe the amount of risk they would tolerate in deciding when to return to sport, how they would approach the rehabilitation process, and the emotional experiences they anticipated having throughout the process. The aim of the first study was to utilize exploratory factor analyses to validate the use of both previously established and newly created questionnaires, including the hypothetical injury scenario. The aim of the second study was to examine the relationships among self-compassion and the dependent variables of risk-taking, recovery strategy preferences, and emotional experiences. Multiple linear regressions were used to assess these relationships while controlling for potential co-variates like athletic identity, personality, and self-esteem.
Participants higher in self-compassion demonstrated a preference for self-protection. Although self-compassion did not influence the amount of risk an athlete was willing to tolerate in returning to their sport, higher levels of self-compassion were associated with a preference for rehabilitation strategies that prioritize preservation and protection over accelerated progress. Self-compassion was also associated with greater positive affect, lower negative affect, and lower uncertainty during recovery. These results were distinct from what could be explained by how participants framed their decisions, personality, and self-esteem.
The results of my research support the self-protection perspective of self-compassion in injury rehabilitation decision-making and add evidence that self-compassion is an adaptive coping mechanism in challenging times. Encouraging self-compassion can help injured athletes navigate an emotionally challenging experience without increasing risk-taking.October 202
Geometric deep learning in drug discovery
No full textArtificial intelligence (AI) is transforming early-stage drug discovery by enabling efficient,
data-driven molecular modeling and prediction. In this thesis, we present a series of interpretable
and task-specific methods grounded in Geometric Deep Learning (GDL) to advance
molecular representation learning across key domains such as molecular property prediction
and drug–target interaction (DTI).
We introduced four original methods that address core challenges in molecular representation
learning. These methods target modality alignment, multiscale feature integration, interpretable
analysis, and target imbalance in regression. Together, they enable the learning of
robust and geometry-aware molecular representations, supporting diverse downstream tasks
under limited or imbalanced data conditions.
To illustrate practical utility, we apply our models to a preliminary virtual screening task for
PIN1 (peptidyl-prolyl cis-trans isomerase NIMA-interacting 1), an oncogenic driver in cancer.
Using a curated dataset with potency and efficacy annotations, we define a composite activity
metric and show the ability of the model to prioritize active compounds.
Together, these contributions demonstrate the versatility of GDL-based approaches in addressing
various molecular learning tasks and their potential to enable interpretable, highperformance
AI frameworks for accelerating drug discovery.October 202
Marcus Agrippa: Co-Emperor of the Roman Empire
No full textThis thesis re-evaluates the political career of Marcus Agrippa (c. 63-12 BCE), arguing that he was not a subordinate agent of Augustus, but a constitutional co-ruler whose authority was publicly acknowledged and proved foundational to the creation of the Roman Principate. It challenges the traditional emperor or ‘great man’ centred narrative by demonstrating that Agrippa’s power—military, civic, legal, and symbolic—was deliberately constructed in parallel with Augustus’ own. By surveying fully Agrippa’s presence within the constitutional, visual, and ritual frameworks of early Empire, this thesis reframes the Principate as a shared construct, co-authored by a statesman whose influence was once visible across the Roman world—and whose legacy was later de-emphasized to serve the needs of dynastic continuity and imperial myth.
This thesis considers a full array of ancient evidence: ancient texts, inscriptions, coinage, architecture, and the ideological performance of power in public ritual. In addition, this study presents the Principate as a constitutional partnership shaped by co-ordinated authority and mutual dependence, rather than by the unilateral supremacy of Augustus. One particular facet of this study is that it proposes a re-examination of ancient Roman sources (often shaped by imperial ideology) alongside Eastern and non-Roman primary sources that have only more recently begun to receive sustained scholarly attention. The former are invaluable in that they testify more openly to Agrippa’s greater role in the construction of the Principate, and therefore their inclusion allows for a more historically accurate picture of Agrippa’s position in the Augustan regime.Manitoba Métis FederationOctober 202
Quantitative portfolio management and financial decision-making with future generation of AI models
No full textThis study investigates Large language models (LLMs) and agentic artificial intelligence (Agentic AI) for their efficacy within the finance domain, particularly focusing on asset allocation, portfolio management, and financial decision-making. Portfolio construction is a complex task that requires careful consideration of multiple asset classes, risk profiles, market conditions, and user-inclusive investment objectives. LLMs and pre-trained models often hallucinate due to their lack of access to real-time and updated information. Additionally, they are not particularly effective at mathematical reasoning. While LLMs exhibit remarkable capabilities in understanding financial terminology and reasoning over structured or unstructured data, they face critical limitations in their access to real-time financial information and market dynamics, which are essential for making informed investment decisions. To address these challenges, our research explores these problems through a three-phase approach: first, the application of advanced prompt engineering techniques; second, the implementation of retrieval-augmented generation (RAG); and finally, the development of a multi-agent system architecture. We show through this research (i) a strong contribution to the intersection of AI and financial decision-making; (ii) that LLMs and agents could act as catalysts for one another rather than relying solely on pre-trained LLMs. Therefore, enhanced performance and more complex execution can be achieved by integrating external agents; (iii) that optimizing the quality and reliability of model-generated responses is possible; (iv) improving the overall effectiveness of financial decision-making processes and portfolio management. As an evaluation mechanism we have done a case-study of comparison with Wealthsimple portfolio classifications by replicating their asset class structure appropriately through our agentic workflow.October 202